Publications

Selected Journal Papers

1. Weiping Ding, Witold Pedrycz, Isaac Triguero, Zehong Cao, and Chin-Teng Lin, “Multigranulation Super-Trust Model for Attribute Reduction,” IEEE Transactions on Fuzzy Systems, 2021, 29(6): 1395-1408. doi:10.1109/ TFUZZ.2020.2975152.  

2. Weiping Ding, Chin-Teng Lin, Mukesh Prasad, Zehong Cao, and Jiandong Wang, “A layered- coevolution-based attribute-boosted reduction using adaptive quantum behavior PSO and its consistent segmentation for neonates brain tissue,” IEEE Transactions on Fuzzy Systems, 2018, 26 (3): 1177-1191. doi:10.1109/TFUZZ.2017.2717381. 

3. Weiping Ding, Mohamed Abdel-Basset, Hossam Hawash, and Witold Pedrycz, “Multimodal Infant Brain Segmentation by Fuzzy-informed Deep Learning,” IEEE Transactions on Fuzzy Systems, 2022, 30(4): 1088-1101. doi:10.1109/TFUZZ.2021. 3052461. 

4. Weiping Ding, Chin-Teng Lin, and Witold Pedrycz, “Multiple relevant feature ensemble selection based on multilayer co-evolutionary consensus MapReduce,” IEEE Transactions on Cybernetics, 2020, 50(2): 425-439. doi:10.1109/TCYB.2018. 2859342.  

5. Weiping Ding, Chin-Teng Lin, and Zehong Cao, “Shared Nearest-neighbor Quantum Game-based Attribute Reduction with Hierarchical Coevolutionary Spark and Its Consistent Segmentation Application in Neonatal Cerebral Cortical Surfaces,” IEEE Transactions on Neural Networks and Learning Systems, 2019, 30 (7): 2013-2027. doi:10.1109/TNNLS. 2018.2872974.

6. Weiping Ding, Shouvik Chakraborty, Kalyani Mali, Sankhadeep Chatterjee, Janmenjoy Nayak, Asit Kumar Das and Soumen Banerjee, “An Unsupervised Fuzzy Clustering Approach for Early Screening of COVID-19 from Radiological Images,” IEEE Transactions on Fuzzy Systems, 2022, 30(8): 2902-2914. doi:10.1109/TFUZZ.2021. 3097806.

7. Weiping Ding, Chin-Teng Lin, and Zehong Cao, “Deep neuro-cognitive co-evolution for fuzzy attribute reduction by quantum leaping PSO with nearest-neighbor memeplexes,” IEEE Transactions on Cybernetics, 2019, 49(7): 2744-2757. doi:10.1109/TCYB.2018. 2834390.

8. Weiping Ding, Chin-Teng Lin, Mukesh Prasad, Senbo Chen, and Zhijin Guan, “Attribute equilibrium dominance reduction accelerator (DCCAEDR) based on distributed co-evolutionary cloud and its application in medical records,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2016, 46(3): 384-400. doi:10.1109/ TSMC.2015.2464787.

9. Weiping Ding, Janmenjoy Nayak, Bighnaraj Naik, Danilo Pelusi, and Manohar Mishra, “Fuzzy and Real Coded Chemical Reaction Optimization for Intrusion Detection in Industrial Big Data Environment,” IEEE Transactions on Industrial Informatics, 2021,17(6): 4298-4307. doi: 10.1109/ TII.2020.3007419. 

10. Weiping Ding, Ming Li, Ying Sun, Jun Liu, Hengrong Ju, Jiashuang Huang, and Chin-Teng Lin, “A Novel Spark-based Attribute Reduction and Neighborhood Classification for Rough Evidence,”IEEE Transactions on Cybernetics, 2024,54(3): 1470-1483. doi: 10.1109/TCYB. 2022.3208130

11. Weiping Ding, Mohamed Abdel-Basset, Khalid A.Eldrandaly, Laila Abdel-Fatah, and Victor Hugo C. de Albuquerque, “Smart Supervision of ‎ Cardiomyopathy based on Fuzzy Harris Hawks Optimizer ‎ and Wearable ‎ Sensing Data Optimization: A New Model,” IEEE Transactions on Cybernetics, 2021,51(10): 4944-4958. doi: 10.1109/TCYB.2020.3000440  . 

12. Weiping Ding, Isaac Triguero, and Chin-Teng Lin, “Co-evolutionary Fuzzy Attribute Order Reduction and Classification Learning with Complete Attribute-value Space Tree,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2021, 5(1): 130-142. doi:10.1109/TETCI.2018. 2869919.  

13. Weiping Ding, Nikhil R. Pal, Chin-Teng Lin, Yiu-ming Cheung, Zehong Cao, Wenjian Luo, “Special Issue on Emerging Computational Intelligence Techniques for Decision Making with Big Data in Uncertain Environments,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2021, 5(1): 2-5. doi: 10.1109/ TETCI.2021.3049701. 

14. Weiping Ding, Yurui Ming, Zehong Cao, and Chin-Teng Lin, “A Generalized Deep Neural Network Approach for Digital Watermarking Analysis,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2022,6(3): 613-627. doi: 10.1109/TETCI. 2021. 3055520.  

15. Weiping Ding, Witold Pedrycz, Gary G. Yen, Bing Xue, “Evolutionary Computation Meets Deep Learning,” IEEE Transactions on Evolutionary Computation, 2021, 25(5): 810-814. doi:10.1109/TEVC.2021.3096336.  

16. Weiping Ding, Shouvik Chakraborty, Kalyani Mali, Sankhadeep Chatterjee, Janmenjoy Nayak, Asit Kumar Das and Soumen Banerjee, “An Unsupervised Fuzzy Clustering Approach for Early Screening of COVID-19 from Radiological Images,” IEEE Transactions on Fuzzy Systems,  2022,30(8): 2902-2914. doi:10.1109/TFUZZ.2021. 3097806.   

17. Weiping Ding, Witold Pedrycz, Gary G. Yen, Bing Xue, “Guest Editorial Evolutionary Computation Meets Deep Learning,”  IEEE Transactions on Evolutionary Computation,  2021, 25(5): 810-814. doi:10.1109/TEVC. 2021. 3096336.  

18. Weiping Ding,  Mohamed Abdel-Basset, Hossam Hawash,  Osama M. Elkomy, “MT-nCov-Net: Multi-Task Deep Learning Framework for Efficient Diagnosis of COVID-19” IEEE Transactions on Cybernetics,  doi: 10.1109/TCYB. 2021.3123173  . 

19. Lin Sun, Lanying Wang, Weiping Ding, Yuhua Qian, and Jiucheng Xu, “Feature Selection Using Fuzzy Neighborhood Entropy-Based Uncertainty Measures for Fuzzy Neighborhood Multi-Granulation Rough Sets,” IEEE Transactions on Fuzzy Systems, 2021, 29(1): 19-33. doi:10.1109/TFUZZ. 2020.2989098  .  (Highly Cited Paper) 

20. Lin Sun, Tengyu Yin, Weiping Ding, Yuhua Qian, and Jiucheng Xu，“Feature Selection with Missing Labels Using Multilabel Fuzzy Neighborhood Rough Sets and Maximum Relevance Minimum Redundancy,” IEEE Transactions on Fuzzy Systems, 2022, 30(5): 1197-1211.  doi:10.1109/TFUZZ.2021. 3053844  .

21. Cuiping Cheng, Weiping Ding, Fuyuan Xiao, and Witold Pedrycz, “A Majority Rule based Measure for Atanassov Type Intuitionistic Membership Grades in MCDM,” IEEE Transactions on Fuzzy Systems. 2022, 30(1): 121-132. doi:10.1109/TFUZZ.2020.3033062.  

22. Liming Fang, Xinyu Yun, Changchun Yin, Weiping Ding, Lu Zhou, Zhe Liu, and Chunhua Su, “ANCS: Automatic NXDomain Classification System based on Incremental Fuzzy Rough Sets Machine Learning,” IEEE Transactions on Fuzzy Systems, 2021, 29 (4): 742-756. doi:10.1109 /TFUZZ.2020. 296587. 

23. Renato W. R. de Souza, Joao V. C. de Oliveira, Leandro A. Passos, Weiping Ding, Joao P. Papa, and Victor Hugo C. de Albuquerque, “A Novel Approach for Optimum-Path Forest Classification Using Fuzzy Logic,” IEEE Transactions on Fuzzy Systems, 2020, 28 (12): 3076-3086. doi: 10.1109/TFUZZ.2019.2949771  .

24. Chongsheng Zhang, Weiping Ding, Guowen Peng, Feifei Fu, and Wei Wang, “Street View Text Recognition with Deep Learning for Scene Understanding in Intelligent Transportation Systems,” IEEE Transactions on Intelligent Transportation Systems. doi: 10.1109/TITS.2020. 3017632.  

25. Ganeshsree Selvachandran, Shio Gai Quek, Luong Thi Hong Lan, Le Hoang Son, Nguyen Long Giang, Weiping Ding, Mohamed Abdel-Basset, and Victor Hugo C. de Albuquerque,  “A New Design of Mamdani Complex Fuzzy Inference System for Multi-attribute Decision Making Problems,” IEEE Transactions on Fuzzy Systems,  2021, 29 (4): 716-730. doi:10.1109/TFUZZ. 2019.2961350    (Highly Cited Paper) 

26. Junqin Huang, Linghe Kong, Hong-Ning Dai, Weiping Ding, Long Cheng, Guihai Chen, Xi Jin, and Peng Zeng, “Blockchain Based Mobile Crowd Sensing in Industrial Systems,” IEEE Transactions on Industrial Informatics, 2020, 16(10): 6553-6563, doi:10.1109/TII. 2019.2963728.  

27. Jieting Wang, Yuhua Qian, Feijiang Li, Jiye Liang, and Weiping Ding, “Fusing Fuzzy Monotonic Decision Trees,” IEEE Transactions on Fuzzy Systems, 2020, 28 (5): 887-900. doi: 10.1109/ TFUZZ.2019.2953024.

28. Muhammad Sajjad, Irfan Tahir, Khan Muhammad, Javier Del Ser, Javier Sanchez-Medina, Sergey Andreev, Weiping Ding, and Jong Weon Lee, “An Efficient and Scalable Simulation Model for Autonomous Vehicles with Economical Hardware,” IEEE Transactions on Intelligent Transportation Systems, 2021, 22(3): 1718-1732. doi: 10.1109/TITS. 2020.2980855  .

29. Zehong Cao, Chin-Teng Lin, Weiping Ding, Mu-Hong Chen, Cheng-Ta Li, and Tung-Ping Su, “Identifying Ketamine Responses in Treatment-Resistant Depression Using a Wearable Forehead EEG,” IEEE Transactions on Biomedical Engineering, 2019, 66(6): 1668-1679. doi:10.1109/TBME.2018.2877651.  

30. Mukesh Prasad, Chin-Teng Lin, Dong-Lin Li, Chao-Tien Hong, Weiping Ding, and Jyh-Yeong Chang, “Soft-boosted self-constructing neural fuzzy inference network,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47(3): 584-588. doi:10.1109/TSMC.2015. 

31. Muhammad Sajjad , Ijaz Ul Haq , Jaime Lloret, Weiping Ding, and Khan Muhammad, “Robust Image Hashing Based Efficient Authentication for Smart Industrial Environment,” IEEE Transactions on Industrial Informatics, 2019,15(12): 6541-6550. doi: 10.1109/TII.2019. 2921652  

32. Muhammad Tariq Sadiq, Xiaojun Yu, Zhaohui Yuan, Muhammad Zulkifal Aziz, Siuly Siuly and Weiping Ding, “A Matrix Determinant Feature Extraction Approach for Decoding Motor and Mental Imagery EEG in Subject Specific Tasks,” IEEE Transactions on Cognitive and Developmental Systems, doi:10.1109/TCDS.2020.3040438.

33. Xinyan Liang, Qian Guo, Yuhua Qian, Weiping Ding, and Qingfu Zhang, “Evolutionary Deep Fusion Method and Its Application in Chemical Structure Recognition” IEEE Transactions on Evolutionary Computation, 2021,25(5): 883-893. doi: 10.1109/ TEVC. 2021.3064943 

34. Ye Shi, Chin-Teng Lin, Yu-Cheng Chang, Weiping Ding, Yuhui Shi, and Xin Yao, “Consensus learning for distributed fuzzy neural network in big data environment,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2021, 5(1): 29-41. doi: 10.1109/TETCI. 2020.2998919  .

35. Akshansh Gupta, Ramesh Kumar Agrawal, Jyoti Singh Kirar, Javier Andrew, Wei-Ping Ding, Chin-Teng Lin, and Mukesh Prasad. “On the utility of Power Spectral Techniques with feature selection Techniques for Effective Mental Task Classification in Non-invasive BCI,” IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2021,51(5): 3080-3092. doi: 10.1109/ TSMC.2019.2917599.

36. Fang-Qi Li, Shi-Lin Wang, Alan Wee-Chung Liew, Weiping Ding, and Gong-Shen Liu, “Large-Scale Malicious Software Classification with Fuzzified Features and Boosted Fuzzy Random Forest,” IEEE Transactions on Fuzzy Systems. 2021, 29(11): 3205-3218. doi: 10.1109/TFUZZ.2020. 3016023  

37. Bo’zena Małysiak-Mrozek, Jadwiga Wieszok, Witold Pedrycz, Weiping Ding, and Dariusz Mrozek, “High-Efficient Fuzzy Querying with HiveQL for Big Data Warehousing,” IEEE Transactions on Fuzzy Systems.  2022, 30(6): 1823-1837. doi:10.1109/ TFUZZ. 2021.3069332. 

38. Jianming Zhan, Jin Ye, Weiping Ding, Peide Liu, “A novel three-way decision model on utility theory in incomplete fuzzy decision systems” IEEE Transactions on Fuzzy Systems. 2022, 30(7): 2210-2216. doi:10.1109/TFUZZ.2021.3078012.   

39. Shiming Chen, Wenjie Wang, Beihao Xia, Xinge You, Qinmu Peng, Zehong Cao, and Weiping Ding, “CDE-GAN: Cooperative Dual Evolution Based Generative Adversarial Network,” IEEE Transactions on Evolutionary Computation. 2021,25(5): 986-1000. doi: 10.1109/TEVC.2021. 3068842. arXiv:2008. 09388v1 [cs.CV] 21 Aug 2020.   

40. Michail Mamalakis, Andrew J. Swift, Bart Vorselaars, Surajit Ray, Simonne Weeks, Weiping Ding, Richard H. Clayton, Louise S. Mackenzie, Abhirup Banerjee, "DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays," CoRR abs/2104.04006 (2021)

41. Wensheng Gan, Zilin Du, Weiping Ding, Chunkai Zhang, Han-Chieh Chao,"Explainable Fuzzy Utility Mining on Sequences," IEEE Transactions on Fuzzy Systems. doi:10.1109/ TFUZZ.2021.3089284.  CoRR abs/2103.16519 (2021). 

42. Jing He, Lei Shen, Yudong Yao, Huaxia Wang, Member, Guodong Zhao, Xiaowei Gu, and Weiping Ding, “Finger Vein Image Deblurring Using Neighbors-based Binary-GAN (NB-GAN) ,” IEEE Transactions on Emerging Topics in Computational Intelligence,  doi: 10.1109/TETCI. 2021.3097734  .

43. Jinkun Chen, Yaojin Lin, Jusheng Mi, Shaozi Li, and Weiping Ding, “A Spectral Feature Selection Approach with Kernelized Fuzzy Rough Sets,” IEEE Transactions on Fuzzy Systems, 2022,30(8): 2886-2901. doi: 10.1109/TFUZZ.2021.3096212  . 

44. Muhammad Tariq Sadiq, Xiaojun Yu, Zhaohui Yuan, Muhammad Zulkifal Aziz, Siuly Siuly and Weiping Ding, “Towards the Development of Versatile Brain-Computer Interfaces,” IEEE Transactions on Artificial Intelligence,  2021, 2(4): 314-328. doi:10.1109/ TAI.2021.3097307.

45. Changzhong Wang, Yuhua Qian, Weiping Ding, Xiaodong Fan, “Feature selection with fuzzy-rough minimum classification error criterion,” IEEE Transactions on Fuzzy Systems, 2022, 30(8): 2930-2942. doi: 10.1109/TFUZZ.2021.309  7811.  

46. Chongsheng Zhang, Yuefeng Tao, Kai Du, Weiping Ding, Bin Wang, Ji Liu, and Wei Wang, “Character-level Street View Text Spotting Based on Deep Multi-Segmentation Network for Safer and Smarter Autonomous Driving” IEEE Transactions on Artificial Intelligence, 2022, 3(2): 297-308.  doi: 10.1109/TAI.2021.3116216.

47. Shuai Liu, Shuai Wang, Xinyu Liu, Jianhua Dai, Khan Muhammad, Amir H. Gandomi, Weiping Ding, Mohammad Hijji, Victor Hugo C.de Albuquerque,  “Human Inertial Thinking Strategy: A Novel Fuzzy Reasoning Mechanism for IoT-Assisted Visual Monitoring,”  IEEE Internet of Things Journal,  doi: 10.1109/JIOT.2022.3142115 

48. Muhammad Tariq Sadiq, Xiaojun Yu, Zhaohui Yuan, Muhammad Zulkifal Aziz, Naveed ur Rehman,  Weiping Ding, Gaoxi Xiao. "Motor Imagery BCI Classification Based on Multivariate Variational Mode Decomposition," IEEE Transactions on Emerging Topics in Computational Intelligence. doi: 10.1109/TETCI.2022.3147030  

49. Linyao Yang, Chen Lv, Xiao Wang, Ji Qiao, Weiping Ding, Jun Zhang, and Fei-Yue Wang,  “Collective Entity Alignment for Knowledge Fusion of Power Grid Dispatching Knowledge Graphs,” IEEE/CAA Journal of Automatica Sinica. 2022, 9(11): 1990–2004. doi: 10.1109/JAS.2022.105947.

50. Zuowei Zhang, Songtao Ye, Yiru Zhang, Weiping Ding, and Hao Wang, “Belief combination of classifiers for incomplete data,” IEEE/CAA Journal of Automatica Sinica，2022, 9(4): 652-667. doi: 10.1109/JAS.2022.105458.

51. Xudong He, Jian Wang, Jiqiang Liu,  Weiping Ding*,  Zhen Han, Bin Wang, Jamel Nebhen, Wei Wang, “DNS Rebinding Threat Modelling and Security Analysis for Local Area Network of Maritime Transportation Systems,” IEEE Transactions on Intelligent Transportation Systems, 2023,24(2):2643-2655. doi:10.1109/TITS.2021.3135197.

52. Diego García-Zamora, Alvaro Labella,  Weiping Ding, Rosa M. Rodríguez, Luis Martínez López, “Large-Scale Group Decision Making: A Systematic Review and a Critical Analysis” IEEE IEEE/CAA Journal of Automatica Sinica， 2022, 9(6): 949-966. DOI: 10.1109/JAS.2022.105617.

53. Shiming Chen, Ziming Hong, Guosen Xie, Qinmu Peng, Xinge You, Weiping Ding, and Ling Shao, “GNDAN: Graph Navigated Dual Attention Network for Zero-Shot Learning,” IEEE Transactions on Neural Networks and Learning Systems,  DOI:10.1109/TNNLS.2022.3155602

54. Fang-Qi Li, Rui-Jie Zhao, Shi-Lin Wang, Li-Bo Chen, Alan Wee-Chung Liew, Weiping Ding, “Online Intrusion Detection for IoT Systems with Full Bayesian Possibilistic Clustering and Ensembled Fuzzy Classifiers,”  IEEE Transactions on Fuzzy Systems, 2022,30(11):4605-4617. doi:10.1109 /TFUZZ.2022.3165390

55. Di Jin, Tao Wang, Rui Wang, Dongxiao He, Weiping Ding, Yuxiao Huang, Longbiao Wang, Witold Pedrycz, “ Amer: A New Attribute-Missing Network Embedding Approach,” IEEE Transactions on Cybernetics,   2023, 53(7): 4306-4319. doi:10.1109/TCYB.2022.3166539  

56. Weihua Xu, Kehua Yuan, Wentao Li, Weiping Ding, “An Emerging Fuzzy Feature Selection Method Using Composite Entropy-Based Uncertainty Measure and Data Distribution,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2023,7(11): 76-88. doi:  10.1109/TETCI.2022. 3171784  

57. Jinghua Liu, Yaojin Lin, Weiping Ding, Hongbo Zhang, and Jixiang Du, “Fuzzy mutual information-based multi-label feature selection with label dependency and streaming labels,” IEEE Transactions on Fuzzy Systems,  2023,31(1): 77-91. doi:10.1109/TFUZZ.2022.3182441  

58. Wentao Liu, Xiaolong Xu, Lianxiang Wu, Lianyong Qi, Alireza Jolfaei, Weiping Ding, Mohammad R. Khosravi, “Intrusion Detection for Maritime Transportation Systems with Batch Federated Aggregation,” IEEE Transactions on Intelligent Transportation Systems,  2023, 24(2): 2503-2514. doi:10.1109/TITS. 2022.3181436 

59. Qiong Chen, Weiping Ding, Xiaomeng Huang, and Hao Wang, “Generalized Interval Type II Fuzzy Rough Model Based Feature Discretization Oriented to Mixed Pixels,” IEEE Transactions on Fuzzy Systems，2023, 31(3): 845-859. doi:10.1109/TFUZZ. 2022.3190625.  

60. Shuwen Wang, Xingquan Zhu, Weiping Ding, Amir Alipour. Yengejeh, “Cyberbullying and Cyberviolence Detection: A Triangular User-Activity-Content View,”  IEEE/CAA Journal of Automatica Sinica, 2022, 9(8): 1384-1405. doi: 10.1109/JAS.2022.105740.

61. Yangyang Zhao, Fuyuan Xiao, Masayoshi Aritsugi, Weiping Ding, “A Quantum Tanimoto Coefficient Fidelity for Entanglement Measurement,” IEEE/CAA Journal of Automatica Sinica, 2023,10(2) 439-450. doi:10.1109/JAS.2022.106079.

62.  Jianming Zhan, Jiajia Wang, Weiping Ding, Yiyu Yao, “Three-way Behavioral Decision Making with Hesitant Fuzzy Information Systems：Survey and Challenges,”  IEEE/CAA Journal of Automatica Sinica, 2023, 10(2): 330-350.  DOI: 10.1109/JAS.2022.106061

63. Weihua Xu, Yanzhou Pan, Xiuwei Chen, Weiping Ding,  and Yuhua Qian, “A Novel Dynamic Fusion Approach Using Information Entropy for Interval-Valued Ordered Datasets,” IEEE Transactions on Big Data, DOI 10.1109/TBDATA.2022.3215494

64. Chuansheng Liu , Weiping Ding, Chun Cheng, Cheng Tang, Jiashuang Huang , and Haipeng Wang, “DenseHashNet: A Novel Deep Hashing for Medical Image Retrieval,”  IEEE Journal of Radio Frequency Identification, doi:10.1109/JRFID.2022.3209986

65. Weihua Xu, Doudou Guo, Yuhua Qian,  Weiping Ding,  “Two-way Concept-cognitive Learning Method: A Fuzzy-based Progressive Learning”, IEEE Transactions on Fuzzy Systems, 2023,31（6):1885-1899. DOI 10.1109/TFUZZ.2022.3216110  

66. Yonglin Tian, Yu Shen, Xiao Wang, Jiangong Wang, Kunfeng Wang, Weiping Ding,  Zilei Wang, and Fei-Yue Wang, “Learning Lightweight Dynamic Kernels with Attention Inside via Local and Global Fusion,”  IEEE Transactions on Neural Networks and Learning Systems, Accepted and to be appeared 

67. Wentao Li, Shichao Zhai, Weihua Xu, Witold Pedrycz,Yuhua Qian, Weiping Ding, and Tao Zhan, “Feature Selection Approach Based on Improved Fuzzy C-Means with Principle of Refined Justifiable Granularity” IEEE Transactions on Fuzzy Systems , DOI: 10.1109/TFUZZ.2022. 3217377  

68. Lin Sun, Tianxiang Wang,  Weiping Ding, and Jiucheng Xu, “Partial Multilabel Learning Using Fuzzy Neighbourhood-Based Ball Clustering and Kernel Extreme Learning Machine,” IEEE Transactions on Fuzzy Systems, DOI: 10.1109/TFUZZ.2022.3222941  

69. Can Gao, Yangbo Wang, Jie Zhou, Weiping Ding, Linlin Shen, Zhihui Lai, “Possibilistic Neighborhood Graph: A New Concept of Similarity Graph Learning, ” IEEE Transactions on Emerging Topics in Computational Intelligence, DOI:10.1109/TETCI.2022.3225173  

70. Jintao Huang, Wenbin Qian, Chi-Man Vong,  Weiping Ding, Wenhao Shu, Qin Huang, “Multi-label Feature Selection via Label Enhancement and Analytic Hierarchy Process”  IEEE Transactions on Emerging Topics in Computational Intelligence, DOI:10.1109/TETCI. 2022.3231655  

71. Weihua Xu, Doudou Guo, Jusheng Mi, Yuhua Qian, Weiping Ding, “A novel approach to two-way concept-cognitive learning via concept movement viewpoint” IEEE Transactions on Neural Networks and Learning Systems, DOI:10.1109/TNNLS.2023.3235800

72. Zuowei Zhang, Songtao Ye, Zechao Liu, Hao Wang, and Weiping Ding, “Deep Hyperspherical Clustering for Skin Lesion Medical Image Segmentation,” IEEE Journal of Biomedical and Health Informatics, 2023,27(8): 3770-3381. DOI:10.1109/JBHI.2023.3240297.

73. Guoxia Xu, Chunming He, Hao Wang, Hu Zhu, and  Weiping Ding, “DM-Fusion: Deep Model-driven Network for Heterogeneous Image Fusion,” IEEE Transactions on Neural Networks and Learning Systems, DOI:10.1109/TNNLS.2023.3238511.

74. Weiping Ding, Mohamed Abdel-Basset, Hossam Hawash, Mahardhika Pratama and Witold Pedrycz,“Generalizable Segmentation of COVID-19 Infection from Multi-Site Tomography Scans: A Federated Learning Framework,” IEEE Transactions on Emerging Topics in Computational Intelligence,2024,8(1): 126-139.  DOI:10.1109/TETCI.2023.3245103.  

75. Guojin Zhong, Weiping Ding,  Long Chen, Guoxia Xu, and Yu-Feng Yu, “Multi-scale Attention Generative Adversarial Network for Medical Image Enhancement ,” IEEE Transactions on Emerging Topics in Computational Intelligence，2023, 7(4): 1113-1125.  DOI:10.1109/TETCI. 2023.3243920.  

76. Pengcheng Zhu, Weiping Ding, Lihua Wei, Shiguang Feng, Xueyun Cheng, Zhijin Guan, “A Variation-Aware Quantum Circuit Mapping Approach Based on Multi-agent Cooperation,” IEEE Transactions on Computers. DOI:10.1109/TC.2023.3242208.

77. Jiayi Sun, Wensheng Gan, Han-Chieh Chao, Philip S. Yu, and Weiping Ding, “Internet of Behaviors: A Survey,” IEEE Internet of Things Journal, 2023, 10(13): 11117-11134. DOI 10.1109/JIOT.2023.3247594.

78. Sibo Cheng, Cesar Quilodr´an-Casas, Said Ouala, Alban Farchi, Che Liu, Pierre Tandeo, ´Ronan Fablet senior member, IEEE, Didier Lucor, Bertrand Iooss, Julien Brajard, Dunhui Xiao, Tijana Pfander,  Weiping Ding, Yike Guo, Alberto Carrassi, Marc Bocquet, Rossella Arcucci, “Machine Learning with data assimilation and uncertainty quantification for dynamical systems: a review ”IEEE/CAA Journal of Automatica Sinica, 2023,10(6):1361-1387. DOI:10.1109/JAS.2023. 123537.

79. Ripon K. Chakrabortty, Mohammad Humyun Fuad Rahman, Weiping Ding, “Guest Editorial: Special Section on Developing Resilient Supply Chains in a Post-COVID Pandemic Era: Application of Artificial Intelligent Technologies for Emerging Industry 5.0,” IEEE Transactions on Industrial Informatics, 2023, 19(3): 3296-3299. DOI: 10.1109/TII.2023.3246645.  

80. Qinghua Zhang, Fan Zhao, Yunlong Cheng, Man Gao, Guoyin Wang, Shuyin Xia and Weiping Ding, “Effective value analysis of fuzzy similarity relation in HQSS for efficient granulation, ” IEEE Transactions on Neural Networks and Learning Systems，DOI: 10.1109/TNNLS.2023.3265310.

81. Zhongyi Cai, Jingya Wang, Jiangnan Tang, Weiping Ding, Chin-Teng Lin, and Ye Shi, “FedTP: Federated Learning by Transformer Personalization,” IEEE Transactions on Neural Networks and Learning Systems, DOI:10.1109/TNNLS.2023.3269062.

82. Li Duan,Yangyang Sun, Wei Ni,  Weiping Ding, Jiqiang Liu,  Wei Wang, “Attacks against Cross-chain Systems and Defense Approaches: A Contemporary  Survey,” IEEE-CAA Journal of Automatica Sinica, Accepted and to be appeared

83. Zhaoyin Shi, Long Chen, Weiping Ding, Chuanbin Zhang, Yingxu Wang “Parameter-Free Robust Ensemble Framework of Fuzzy Clustering,” IEEE Transactions on Fuzzy Systems，2023, 31(12): 4205-4219. DOI: 10.1109/TFUZZ.2023.3277692  

84. Qiong Chen, Liangru Xie, Lirong Zeng, Sining Jiang, Weiping Ding*, Xiaomeng Huang, and Hao Wang*,  “Neighborhood Rough Residual Network Based Outlier Detection Method in IoT-Enabled Maritime Transportation Systems,” IEEE Transactions on Intelligent Transportation Systems，DOI: 10.1109/TITS.2023.3285615

85. Li Duan,Yangyang Sun, Wei Ni, Weiping Ding, Jiqiang Liu,  Wei Wang, “Attacks against Cross-chain Systems and Defense Approaches: A Contemporary  Survey,” IEEE-CAA Journal of Automatica Sinica  Accepted and to be appeared

86. Imran Razzak, Reda Bouadjenk, Brij B. Gupta,  Weiping Ding, “Support Matrix Machine via Joint l2,1 and Nuclear Norm Minimization Under Matrix completion Framework for Classification of Corrupted Data,”  IEEE Transactions on Neural Network and Learning System. DOI: 10.1109/TNNLS.2023.3293888

87. Bin Yu, Hengjie Xie, Mingjie Cai, Weiping Ding, “MG-GCN: Multi-granule graph convolution neural network for multi-label classification,” IEEE Transactions on  Emerging Topics in Computational Intelligence, 2024,8(1): 288-299. DOI: 10.1109/TETCI.2023.3300303  

88. Yaojin Lin, Zhuoxin He, Guo Lei, XueGang Hu,Weiping Ding, “Multi-label Feature Selection via Positive or Negative Correlation,” IEEE Transactions on  Emerging Topics in Computational Intelligence, 2024,8(1): 401-415. DOI: 10.1109/TETCI.2023.3302653  

89. Chenglong Zhu, Xueling Ma, Weiping Ding, Jianming Zhan, “Long-term time series forecasting with multi-linear trend fuzzy information granules for LSTM in a periodic framework,” IEEE Transactions on Fuzzy Systems, 2024,32(1):322-336. DOI: 10.1109/TFUZZ.2023.3298970  

90. Wanli Huang, Yanhong She, Xiaoli He, Weiping Ding, “Fuzzy Rough Sets-Based Incremental Feature Selection for Hierarchical Classification,” IEEE Transactions on Fuzzy Systems, 2023, 31(10): 3721-3733. DOI: 10.1109/TFUZZ.2023.3300913  

91. Hengrong Ju, Tan Yin, Jiashuang Huang, Weiping Ding, Xibei Yang, “Sparse mutual granularity based feature selection and its application of schizophrenia patients,”  IEEE Transactions on Emerging Topics in Computational Intelligence, DOI: 10.1109/TETCI.2023.3314548  

92. Shiming Chen, Shuhuang Chen, Wenjin Hou, Weiping Ding, and Xinge You, “EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learning,” IEEE Transactions on Evolutionary Computation,  DOI: 10.1109/TEVC.2023.3307245  

93. Jianhua Dai, Tao Chen, Kai Zhang, Dun Liu, Weiping Ding, “GIFTWD: A prospect theory-based generalized intuitionistic fuzzy three-way decision model, ” IEEE Transactions on Fuzzy Systems, DOI: 10.1109/TFUZZ.2023.3311624  

94. Junhao Huang,Yuhui Deng, Ke Wang, Zhangwei Li, Zhimin Tang,  Weiping Ding, “UnbiasNet: Vehicle Re-Identification Oriented Unbiased Feature Enhancement by Using Causal Effect,” IEEE Transactions on Intelligent Transportation Systems,2024,25(4): 1925-1937. DOI: 10.1109/TITS.2023.3317294

95. Di Wang, Zhuoran Zheng, Weiping Ding, Xiuyi Jia, “LGABL: UHD Multi-Exposure Image Fusion via Local and Global Aware Bilateral Learning,” IEEE Transactions on Emerging Topics in Computational Intelligence. DOI: 10.1109/TETCI.2023.3327397  

96. Shuyin Xia, Cheng Wang, Guoyin Wang, Weiping Ding, Xinbo Gao, Jianhang Yu, Yujia Zhai, Zizhong Chen,“GBRS: A Unified Granular-ball Learning Model of Pawlak Rough Set and Neighborhood Rough Set,”  IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2023.3325199 

97. Dandan Zhu, Kun Zhu,Weiping Ding,Nana Zhang, Xiongkuo Min, Guangtao Zhai, Xiaokang Yang, “MTCAM: A Novel Weakly-supervised Audio-visual Saliency Prediction Model with Multi-modal Transformer,” IEEE Transactions on Emerging Topics in Computational Intelligence. DOI: 10.1109/TETCI.2024.3358184

98. Yang Zhang, Yu-Feng Yu, Long Chen, and Weiping Ding, “Robust Correlation Filter Learning with Continuously Weighted Dynamic Response for UAV Visual Tracking,” IEEE Trans. on Geoscience and Remote Sensing，2023, 61: 4705814. DOI: 10.1109/TGRS.2023.3325337

99. Doudou Guo, Weihua Xu, Yuhua Qian, Weiping Ding, “Fuzzy-granular Concept-cognitive Learning via Three-way Decision: Performance Evaluation on Dynamic Knowledge Discovery,” IEEE TFS Transactions on Fuzzy Systems. 2024, 32(3)：1409-1423. DOI: 10.1109/TFUZZ. 2023.3325952  

100. Weiping Ding, Yu Geng, Jiashuang Huang, Hengrong Ju, Haipeng Wang, Chin-Teng Lin, “MGRW-Transformer: Multi-Granularity Random Walk Transformer Model For Interpretable Learning,”  IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2023. 3326283

101. Changzhong Wang,Yan Wang, Tingquan Deng , Weiping Ding, and Yuhua Qian“Low-ranked multi-label learning based on nonlinear mapping,” IEEE Transactions on Artificial Intelligence, DOI: 10.1109/TAI.2023.3329079

102. Che Liu, Sibo Cheng, Weiping Ding, and Rossella Arcucci, “Spectral Cross-Domain Neural Network with Soft-adaptive Threshold Spectral Enhancement,” IEEE Transactions on Neural Networks and Learning Systems,DOI: 10.1109/TNNLS.2023.3332217

103. Hui Zhang, Guiyang Luo, Xiao Wang, Yidong Li, Weiping Ding, and Fei-Yue Wang, “SASAN: Shape-Adaptive Set Abstraction Network for Point-Voxel 3D Object Detection,” IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS. 2023.3339889

104. Abdul Qayyum, Imran Razzak, Moona Mazher, Tariq Khan, Weiping Ding, and Steven Niederer，“Two-Stage Self-Supervised Contrastive Learning Aided Transformer for Real-Time Medical Image Segmentation,” IEEE Journal of Biomedical and Health Informatics, DOI:10.1109 /JBHI.2023.3340956

105. Yonglin Tian, Xianjing Zhang, Xiao Wang, Jintao Xu, Jiangong Wang, Rui Ai, Weihao Gu, Weiping Ding, "ACF-Net: Asymmetric Cascade Fusion for 3D Detection with LiDAR Point Clouds and Images," IEEE Transactions on Intelligent Vehicles, DOI: 10.1109/TIV.2023.3341223

106. Xinjie Zhu, Yan Zhong, Zidong Wang, Weiguo Sheng, Weiping Ding , Bingbing  Jiang,  "Discriminative Multi-view Fusion via Adaptive Regression," IEEE Transactions on  Emerging Topics in Computational Intelligence, DOI: 10.1109/TETCI.2024.3375342

107. Weiping Ding, Chuansheng Liu, Jiashuang Huang, Chun Cheng, and Hengrong Ju, “ViTH-RFG: Vision Transformer Hashing with Residual Fuzzy Generation for Targeted Attack in Medical Image Retrieval,” IEEE Transactions on Fuzzy Systems, DOI: 10.1109/TFUZZ.2023.3343352  

108. Shu Jiang, Zuchao Li, Hai Zhao, and Weiping Ding, “Entity-Relation Extraction as Full Shallow Semantic Dependency Parsing, ” IEEE Transactions on Audio, Speech, and Language Processing , DOI: 10.1109/TASLP.2024.3350905

109. Kun Zhu, Nana Zhang, Weiping Ding, and Changjun Jiang, "An Adaptive Heterogeneous Credit Card Fraud Detection Model Based on Deep Reinforcement Training Subset Selection," IEEE Transactions on Artificial Intelligence, DOI: 10.1109/TAI.2024.3359568

110. Cheng Tang, Junkai Ji, Yuki Todo, Weiping Ding Sachiko Kodera, and Akimasa Hirata, “Dendritic neural network: a novel extension of dendritic neuron model,” IEEE Transactions on Emerging Topics in Computational Intelligence,DOI: 10.1109/TETCI.2024. 3367819 

111. Qin Xie, Qinghua Zhang, Chengying Wu, Shuyin Xia, Guoyin Wang, Weiping Ding, “GBG++: A Fast and Stable Granular Ball Generation Method for Classification,”  IEEE Transactions on Emerging Topics in Computational Intelligence，DOI: 10.1109/TETCI.2024.3359091  

112. M.Victoria Luzón, Nuria Rodríguez-Barroso, Alberto Argente-Garrido, Daniel Jiménez López, Jose M. Moyano, Javier Del Ser, Weiping Ding, Francisco Herrera,  “A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends,” IEEE/CAA Journal of Automatica Sinica 2024, DOI: 10.1109/JAS.2024.124215

113. Ke Wang,  Mingjia Zhu, Zicong Chen, Jian Weng, Ming Li, Siu-Ming Yiu, Weiping Ding,Tianlong Gu, “A Statistical Physics Perspective: Understanding the Causality Behind Convolutional Neural Network Adversarial Vulnerability,” IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2024.3359269.

114. Huashi Zhu, Dexuan Xu, Yu Huang∗, Zhi Jin, Weiping Ding, Jiahui Tong, Guoshuang Chong “Graph Structure Enhanced Pre-training Language Model for Knowledge Graph Completion,”  IEEE Transactions on Emerging Topics in Computational Intelligence. DOI: 10.1109/TETCI. 2024.3372442

115. Yuting Zhou, Can Gao, Jie Zhou, Weiping Ding, Linlin Shen, and Zhihui Lai,  “OCI-SSL: Open Class-Imbalanced Semi-Supervised Learning with Contrastive Learning,” IEEE Transactions on Emerging Topics in Computational Intelligence. DOI: 10.1109/TETCI.2024.3372436.

116. Yi Ding, Weihua Xu, Weiping Ding, Yuhua Qian, “IFCRL:Interval-intent Fuzzy Concept Re-cognition Learning,” IEEE Transactions on Fuzzy Systems. DOI: 10.1109/TFUZZ.2024. 3376569

117. Hong Zhao, Yuling Su, Zhiping Wu, Weiping Ding, “CSTS: Exploring Class-specific and Task-shared Embedding Representation for Few-shot Learning,” IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2024.3380833

118. Pengrui Liu, Wei Wang, Xiangrui Xu, Hanxi Li, and Weiping Ding, “Assessing Membership Leakages via Task-Aligned Divergent Shadow Datasets in Vehicular Road Cooperation,” IEEE Internet of Things Journal. DOI: 10.1109/JIOT.2024.3380642

119. Dandan Zhu, Kun Zhu, Weiping Ding, Nana Zhang, Kaiwei Zhang, Jiabao Zhao, Guangtao Zhai, Xiaokang Yang,” From Discrete Representation to Continuous Modeling: A Novel Audio-visual Saliency Prediction Model with Implicit Neural Representations,”IEEE Transactions on Emerging Topics in Computational Intelligence. DOI: 10.1109/TETCI.2024.3386619

120. Hengrong Ju, Tingting Shan, Weiping Ding, Keyu Liu, Muhammad Jabir Khan, Jiashuang Huang, Xibei Yang, “BiFuG2-Spark: Bi-directional Fuzzy Granular-Cabin Parallel Attribute Reduction Accelerator with Granular-Group Collaboration,” IEEE Transactions on Fuzzy Systems. DOI: 10.1109/TFUZZ.2024.3392328

121. Zhaoyin Shi, Long Chen, Weiping Ding,  Guang-yong Chen, Chuanbin Zhang, Yingxu Wang, C. L. Philip Chen, “IFKMHC: Implicit Fuzzy K-Means Model for High-Dimensional Data Clustering,” IEEE Transactions on Cybernetics. DOI: 10.1109/TCYB.2024.3391274

122. Dongyuan Li, Zhen Wang, Yankai Chen, Weiping Ding, Manabu Okumura, “A Survey on Deep Active Learning: Recent Advances and New Frontiers,” IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2024.3396463

123. Lin Sun, Tianxiang Wang, Weiping Ding,  Yuhua Qian, Jiucheng Xu, “FCPFS: Fuzzy Granular Ball Clustering-Based Partial Multilabel Feature Selection with Fuzzy Mutual Information,” IEEE Transactions on Emerging Topics in Computational Intelligence. DOI: 10.1109/TETCI.2024.3399665

124. Fevrier Valdez, Oscar Castillo, and Patricia Melin, Weiping Ding, “A survey on Type-3 Fuzzy Logic Systems and its control applications,” IEEE/CAA Journal of Automatica Sinica. DOI: 10.1109/JAS.2024.124530

125. Wenbin Qian, Yihui Li, Qianzhi Ye, Shuyin Xia, Jintao Huang, and Weiping Ding, “Confidence-Induced Granular Partial Label Feature Selection via Dependency and Similarity,”IEEE Transactions on Knowledge and Data Engineering. DOI: 10.1109/TKDE. 2024.3405489

126. Bo˙zena Małysiak-Mrozek, Bartłomiej Ryba, Marek Moleda, Che-Lun Hung, Witold Pedrycz, Weiping Ding, Dariusz Mrozek, “Interpreting Industrial IoT Data Streams through Fuzzy Querying with Hysteretic Fuzzy Sets on Apache Kafka,” IEEE Transactions on Fuzzy Systems. DOI: 10.1109/TFUZZ.2024.3409585

127. Weiping Ding, Tianyi Zhou, Jiashuang Huang, Shu Jiang, Tao Hou, Chin-Teng Lin, “FMDNN: A Fuzzy-guided Multi-granularity DeepNeural Network for Histopathological Images Classification,”IEEE Transactions on Fuzzy Systems. DOI: 10.1109/TFUZZ.2024.3410929

128. Shanliang Yao, Runwei Guan, Zhaodong Wu, Yi Ni, Zile Huang, Zixian Zhang,Yong Yue, Weiping Ding, Hyungjoon Seo, Ka Lok Man, Xiaohui Zhu, Yutao Yue,“WaterScenes: A Multi-Task 4D Radar-Camera Fusion Dataset and Benchmark for Autonomous Driving on Water Surfaces” IEEE Transactions on Intelligent Transportation Systems. DOI: 10.1109/TITS.2024.3415772

129. Yuepeng Chen, Weiping Ding, Hengrong Ju, Jiashuang Huang, and Tao Yin,“Cascaded two-stage feature clustering and selection via separability and consistency in fuzzy decision systems," IEEE Transactions on Fuzzy Systems. DOI: 10.1109/TFUZZ.2024.3420963

130. Kehua Yuan, Duoqian Miao, Witold Pedrycz,  Weiping Ding, Hongyun Zhang,“Ze-HFS: Zentropy-Based Uncertainty Measure for Heterogeneous Feature Selection and Knowledge Discovery,”IEEE Transactions on Knowledge and Data Engineering. DOI: 10.1109/TKDE.2024.3419215

131. Jinbo Li, Peng Liu, Long Chen,Witold Pedrycz, Weiping Ding,“An Integrated Fusion Framework for Ensemble Learning Leveraging Gradient Boosting and Fuzzy Rule-Based Models,” IEEE Transactions on Artificial Intelligence. DOI: 10.1109/TAI.2024.3424427

132. Haibin Ouyang, Dongmei Liu, Steven Li, Weiping Ding, Zhi-hui Zhan,“Two-Stage Deep Feature Selection Method Using Voting Differential Evolution Algorithm for Pneumonia Detection from Chest X-Ray Images,”IEEE Transactions on Emerging Topics in Computational Intelligence, DOI: 10.1109/TETCI.2024.3425285

133. Yingbai Hu, Wei Zhou, Yueyue Liu, Minghao Zeng, Weiping Ding, Shu Li, Guoxin Li, Zheng Li, Alois Knoll, “Efficient Online Planning and Robust Optimal Control for Nonholonomic Mobile Robot in Unstructured Environments,” IEEE Transactions on Emerging Topics in Computational Intelligence. DOI: 10.1109/TETCI.2024.3424527

134. Yijie Ding, Prayag Tiwari, Fei Guo, Quan Zou, and Weiping Ding, “Fuzzy neural tangent kernel model for identifying DNA N4-methylcytosine sites,” IEEE Transactions on Fuzzy Systems, DOI:10.1109/TFUZZ.2024.3425616.

135. Yijie Ding, Prayag Tiwari, Fei Guo, Quan Zou, and Weiping Ding, “Fuzzy neural tangent kernel model for identifying DNA N4-methylcytosine sites,”IEEE Transactions on Fuzzy Systems, DOI:10.1109/TFUZZ.2024.3425616

136. Weiping Ding, Haipeng Wang, Jiashuang Huang, Hengrong Ju, Yu Geng, Chin-Teng Lin, and Witold Pedrycz, “FTransCNN: Fusing Transformer and a CNN based on Fuzzy Logic for Uncertain Medical Image Segmentation,” Information Fusion 99 (2023) 101880. doi: https://doi.org/10.1016/j.inffus.2023.101880  

137. Ziqiang Gao, Linlin Zhou, Weiping Ding, Haipeng Wang,"A Retinal Vessel Segmentation Network Approach based on Rough Sets and Attention Fusion Module," Information Sciences, 678 (2024) 121015. https://doi.org/10.1016/j.ins.2024.121015

138. Weiping Ding, Sheng Geng, Haipeng Wang, Jiashuang Huang, Tianyi Zhou,”FDiff-Fusion: Denoising diffusion fusion network based on fuzzy learning for 3D medical image segmentation,” Information Fusion 112 (2024) 102540. https://doi.org/10.1016/ j.inffus.2024.102540

139. Weiping Ding, Ying Sun, Jiashuang Huang, Hengrong Ju, Chongsheng Zhang,  Guang Yang, and   Chin-Teng Lin, “RCAR-UNet: Retinal Vessel Segmentation Network Algorithm via Novel Rough Attention Mechanism,”  Information Sciences, 657 (2024) 120007. https://doi.org/10.1016 /j.ins.2023.120007

140. Junwei Duan, Jiaqi Xiong, Yinghui Li  and Weiping Ding, “Deep learning based multimodal biomedical data fusion: An overview and comparative review,” Information Fusion，112 (2024) 102536. https://doi.org/10.1016/j.inffus.2024.102536

141. Chenlu Zhu, Xiaodi Liu, Weiping Ding, Shitao Zhang Hao Xu,”Cloud model-based multi-stage multi-attribute decision-making method under probabilistic interval-valued hesitant fuzzy environment,” Expert Systems with Applications 255 (2024) 124595. https://doi.org/ 10.1016/j.eswa.2024.124595

142. Yupeng Wang, Can Xu, Yongli Wang, Xiaoli Wang, and Weiping Ding, “Adversarially Attack Feature Similarity for FineGrained Visual Classification,” Applied Soft Computing Journal 163 (2024) 111945. https://doi.org/10.1016/j.asoc.2024.111945 

143. Weiping Ding,  Ibrahim Alrashdi, Hossam Hawash and Mohamed Abdel-Basset，“DeepSecDrive: An Explainable Deep Learning Framework for Real-Time Detection of Cyberattack in In-Vehicle Networks” Information Sciences, 658 (2024) 120057. https://doi.org/10.1016/j.ins.2023.120057  

144. Lin Sun, Qifeng Zhang, Weiping Ding, Jiucheng Xu, “Fuzzy Neighborhood-Based Manifold Learning and Feature Weight Matrix for Multilabel Feature Selection”Knowledge-Based Systems  299 (2024) 112125. https://doi.org/10.1016/j.knosys.2024.112125

145. Yuepeng Chen, Weiping Ding, Hengrong Ju, Jiashuagn Huang, Tao Yin, “A Distributed Attribute Reduction based on Neighborhood Evidential Conflict Rate with Apache Spark,” Information Sciences, 668 (2024) 120521. https://doi.org/10.1016/j.ins.2024.120521

146. Yaxin Hou, Weiping Ding, Chongsheng Zhang, "imFTP: Deep Imbalance Learning via Fuzzy Transition and Prototypical Learning,” Information Sciences,679 (2024) 121071. https://doi.org/10.1016/j.ins.2024.121071

147. Guangming Lang, Weiping Ding, Duoqian Miao, Hamido Fujita, Yiyu Yao, “Trisection-fusion and fusion-trisection methods of three-way conflict analysis with Pythagorean fuzzy information,” Applied Soft Computing  164 (2024) 111939.  https://doi.org/10.1016/j.asoc.2024.111939

148. Jicun Jiang, Xiaodi Liu, Zengwen Wang, Weiping Ding, Shitao Zhang“Large group decision-making with a rough integrated asymmetric cloud model under multi-granularity linguistic environment,” Information Sciences,678 (2024) 120994.  https://doi.org/10.1016/j.ins. 2024.120994 

149. Xiaoyang Wei, Zhiyuan Li, Yuanyuan Tian, Mengxiao Wang, Weiping Ding,Jinlei Liu, Yanrui Jin, Chengliang Liu,“Differentiated Knowledge Distillation: Patient-Specific Single-Sample Personalization for Electrocardiogram Diagnostic Models,"Engineering Applications of Artificial Intelligence,136 (2024) 108880.  https://doi.org/10.1016/j.engappai. 2024.108880

150. Weiping Ding, Hongcheng Yao, Hengrong Ju, Jiashuang Huang, Shu Jiang, Yuepeng Chen,“Pheromone-Guided Parallel Rough Hypercuboid Attribute Reduction,”  Applied Soft Computing 156 (2024) 111479.   https://doi.org/10.1016/j.asoc.2024.111479

151. Doudou Guo, Weihua Xua, Weiping Ding, Yiyu Yao, Xizhao Wang, Witold Pedrycz, Yuhua Qian,“Concept-Cognitive Learning Survey: Mining and Fusing Knowledge from Data,”Information Fusion 109 (2024) 102426.https://doi.org/10.1016/j.inffus.2024.102426

152. Sheng Li,  Yadong Xu,  Ke Feng,  Yongbo Li, Ke Zhang, Yulin Wang, Weiping Ding, ”Cross-Modal Zero-Sample Diagnosis Framework Utilizing Non-Contact Sensing Data Fusion,”Information Fusion 110 (2024) 102453. https://doi.org/10.1016/j.inffus.2024.102453

153. Cong Huang, Serdar Coskun, Hamid Reza Karimi, Weiping Ding,"A Distributed State and Fault Estimation Scheme for State-Saturated Systems With Quantized Measurements Over Sensor Networks," Information Fusion,110 (2024) 102452. https://doi.org/10.1016 /j.inffus.2024.102452

154. Hengrong Ju, Xiaoxue Fan, Weiping Ding, Jiashuang Huang, Witold Pedrycz, Xibei Yang，“Multi-association evidential feature selection and its application to identifying schizophrenia,”Information Sciences 674 (2024) 120647. https://doi.org/10.1016 /j.ins.2024.120647

155. Shancheng Jiang, Zehui Wu, Kun Xiang, Weiping Ding, Zhen-Song Chen,“A Prior Knowledge-guided Distributionally Robust Optimization-based Adversarial Training Strategy for Medical Image Classification,” Information Sciences  673 (2024) 120705.  https://doi.org/10.1016/j.ins.2024.120705

156. Salama A. Mostafa, Sharran Ravi, Dilovan Asaad Zebari, Nechirvan Asaad Zebari, Mazin Abed Mohammed, Jan Nedoma, Radek Martinek, Muhammet Deveci, Weiping Ding，“A YOLO-based deep learning model for Real-Time face mask detection via drone surveillance in public spaces,”Information Sciences，676 (2024) 120865.  https://doi.org/10.1016/j.ins.2024.120865

157. Jing Chen, Shengyi Yang, Weiping Ding, Peng Li, Aijun Liu, Hongjun Zhang, Tian Li,” Incremental high average-utility itemset mining: survey and challenges,” Scientific Reports (2024) 14:9924. https://doi.org/10.1038/s41598-024-60279-0

158. Changzhong Wang, Shibing Pei, Xiang Lv, Weiping Ding,“Multiscale collaborative representation for face recognition via class-information fusion,” Pattern Recognition  154 (2024) 110586. https://doi.org/10.1016/j.patcog.2024.110586

159. Xiaoling Wu, Yu-Feng Yu, Long Chen; Weiping Ding, Yingxu Wang, ”Robust Deep Fuzzy K-means Clustering for Image Data,”Pattern Recognition, 153 (2024) 110504.  https://doi.org/10.1016/j.patcog.2024.110504 

160. Sher Lyn Tan, Ganeshsree Selvachandran, Raveendran Paramesran,Weiping Ding,“Lung Cancer Detection Systems Applied to Medical Images: A State-of-the-Art Survey,” Archives of Computational Methods in Engineering. https://doi.org/10.1007/s11831-024-10141-3

161. Rongtao Zhang, Xueling Ma, Chao Zhang, Weiping Ding, Jianming Zhan, “GA–FCFNN: A new forecasting method combining feature selection methods and feedforward neural networks using genetic algorithms,” Information Sciences 669 (2024) 120566.  https://doi.org/10.1016/j.ins.2024.120566

162. Yingbai Hu, Fares J. Abu-Dakka, Fei Chen, Xiao Luo,  Zheng Li, Alois Knoll and Weiping Ding,”A Comprehensive Survey of Imitation Learning from Demonstrations: Machine Learning Fusion with Dynamical System,” Information Fusion 108 (2024) 102379. https://doi.org/10.1016/j.inffus.2024.102379 

163. Yunfei He, Li Meng, Jian Ma, Yiwen Zhang, Qun Wu, Weiping Ding, Fei Yang, “Hierarchical Bottleneck for Heterogeneous Graph Representation,” Information Sciences 667 (2024) 120422. https://doi.org/10.1016/j.ins.2024.120422 

164. Changzhong Wang, Yan Wang, Tingquan Deng, Weiping Ding, “Missing multi-label learning based on the fusion of two-level nonlinear mappings,” Information Fusion 103 (2024) 102105. https://doi.org/10.1016/j.inffus.2023.102105  

165. Yanli Li, Weiping Ding, Huaming Chen, Wei Bao, Dong Yuan, “Contribution-Wise Byzantine-Robust Aggregation for Class-Balanced Federated Learning”Information Sciences, 667 (2024) 120475. https://doi.org/10.1016/j.ins.2024.120475

166. Yuxin Zhao, Xiaobo Li, Changjun Zhou, Hao Peng, Jun Chen, Zhonglong Zheng, Weiping Ding, A Review of Cancer Data Fusion Methods Based on Deep Learning Information Fusion, https://doi.org/10.1016/j.inffus.2024.102361

167. Lin Sun, Yuxuan Ma, Weiping Ding, Jiucheng Xu, “SFSLH: Sparse Feature Selection with Local Feature Correlation and High-order Label for Multilabel Learning,” Applied Intelligence https://doi.org/10.1007/s10489-023-05136-9

168. Lin Sun, Yuxuan Ma, Weiping Ding, Zhihao Lu, Jiucheng Xu, “LSFSR: Local Label Correlation-Based Sparse Multilabel Feature Selection with Feature Redundancy” Information Sciences, https://doi.org/10.1016/j.ins.2024.120501

169. Wenbin Qian, Yinsong Xiong, Weiping Ding, Jintao Huang and Chi-Man Vong, “Label Correlations-based Multi-label Feature Selection with Label Enhancement,” Engineering Applications of Artificial Intelligence 127 (2024) 107310. https://doi.org/ 10.1016/j.engappai. 2023.107310 

170. Shuai Liu, Yating Li, Yunhe Wang, Weina Fu, Weiping Ding, “Solution of Wide and Micro Background Bias in Contrast Action Representation Learning,” Engineering Applications of Artificial Intelligence 133 (2024) 108244. https://doi.org/10.1016/j.engappai.2024.108244

171. Hengrong Ju, Yang Lu, Weiping Ding,  Jinxin Cao, Xibei Yang,” Three-way evidence theory-based density peak clustering with the principle of justifiable granularity” Applied Soft Computing https://doi.org/10.1016/j.asoc.2023.111217

172. Xiangrui Li, Dongxu Wei, Xiyuan Hu,Liming Zhang,  Weiping Ding, Wen-Liang Hwang, Zhenmin Tang, “Statistical Guarantees for Noisy Tensor Recovery by Fusing Low-rankness on All Orientations in Frequency-original Domains,” Information Fusion，106 (2024) 102262. DOI: 10.1016/j.inffus. 2024.102262  

173. Boyuan Zhang, Yucheng Shi, Yahong Han, Qinghua Hu,Weiping Ding, “Cascade & Allocate: A Cross-structure Adversarial Attack against Models Fusing Vision and Language,” Information Fusion，https://doi.org/10.1016/j.inffus.2023.102179  

174. Gleb Beliakov, Jian-Zhang Wu, Weiping Ding, “Representation, optimization and generation of fuzzy measures, ” Information Fusion, https://doi.org/10.1016/j.inffus.2024.102295  

175. Bin Yu, Ruihui Xu, Mingjie Cai, Weiping Ding, “A clustering method based on multi-positive-negative granularity and attenuation-diffusion pattern,” Information Fusion, 103 (2024) 102137. https://doi.org/10.1016/j.inffus.2023.102137  

176. Bo Liu, Lejian He, Yuchen Xie, Yuejia Xiang, Li Zhu, Weiping Ding, “Min-JoT: Multimodal infusion Joint Training for Noise Learning in Text and Multimodal Classification Problems," Information Fusion, https://doi.org/10.1016/j.inffus.2023.102071  

177. Rong Jiang, Rui Liu, Tao Zhang, Weiping Ding, Shenghu Tian “An Electronic Medical Record Access Control Model Based on Intuitionistic Fuzzy Trust,” Information Sciences 658 (2024) 120054 https://doi.org/10.1016/j.ins.2023.120054  

178. Xuming Han, Yali Chu, Ke Wang, Limin Wang, Lin Yue, Weiping Ding,  “TAILOR: inTer-feAture distinctIon fiLter fusiOn pRuning,”Information Sciences 665 (2024) 120229. https://doi.org/ 10.1016/j.ins.2024.120229 

179. Weiping Ding, Mohamed Abdel-Basset, Ibrahim Alrashdi, and Hossam Hawash, “Next generation of Computer Vision for Plant Disease Monitoring in Precision Agriculture: A Contemporary Survey, Taxonomy, Experiments, and Future Direction, Information Sciences 665 (2024) 120338.  https://doi.org/10.1016/j.ins.2024.120338

180. Xiao Wang, Yutong Wang, Jing Yang, Xiaofeng Jia, Lijun Li, Weiping Ding, Fei-Yue Wang, "The Survey on Multi-Source Data Fusion in Cyber-Physical-Social Systems: Foundational Infrastructure for Industrial Metaverses and Industries 5.0,”  Information Fusion 107 (2024) 102321. https://doi.org/10.1016/j.inffus.2024.102321 

181. Zhimeng Xin, Shiming Chen, Tianxu Wu, Yuanjie Shao, Weiping Ding, Xinge You,”Few-Shot Object Detection: Research Advances and Challenges,” Information Fusion 107 (2024) 102307  https://doi.org/10.1016/j.inffus.2024.102307

182. Hangming Zhang, Hanping Hu, Weiping Ding, “VSDHS-CIEA: Color image encryption algorithm based on novel variable-structure discrete hyperchaotic system and cross-plane confusion strategy,” Information Sciences 665 (2024) 120332. https://doi.org/10.1016/j.ins.2024.120332

183. Bin Yu, Zijian Zheng, Mingjie Cai, Witold Pedrycz, Weiping Ding, “FRCM: A fuzzy rough c-means clustering method,” Fuzzy Sets and Systems. https://doi.org/10.1016/j.fss.2024.108860

184. Ming Li, Xiaosheng Zhuang, Lu Bai, Weiping Ding,”Multimodal Graph Learning Based on 3D Haar Semi-Tight Framelet for Student Engagement Prediction,” Information Fusion 105 (2024) 102224  https://doi.org/10.1016/j.inffus.2024.102224 

185. Yinxin Bao; Qinqin Shen; Yang Cao; Weiping Ding, Quan Shi,” Residual Attention Enhanced Time-Varying Multi-Factor Graph Convolutional Network for Traffic Flow Prediction,” Engineering Applications of Artificial Intelligence, 133 (2024) 108135，https://doi.org/ 10.1016/j.engappai.2024.108135 

186. [1Xunjin Wu, Jianming Zhan, Tianrui Li, Weiping Ding, Witold Pedrycz, “MBSSA-Bi-AESN: Classification prediction of bi-directional adaptive echo state network based on modified binary salp swarm algorithm and feature selection,” Applied Intelligence, https://doi.org/10.1007 /s10489-024-05280-w

187. Wenbin Qian, Yanqiang Tu, Jintao Huang  and Weiping Ding,  “Partial Multi-Label Learning via Robust Feature Selection and Relevance Fusion Optimization,” Knowledge-Based Systems 286(7):111365. DOI: 10.1016/j.knosys.2023.111365

188. Nana Han, Junsheng Qiao, Tengbiao Li, Weiping Ding,” Multigranulation fuzzy probabilistic rough sets induced by overlap functions and their applications,” Fuzzy Sets and Systems https://doi.org/10.1016/j.fss.2024.108893 

189. Sher Lyn Tan, Ganeshsree Selvachandran, Weiping Ding, Raveendran Paramesran & Ketan Kotecha, “Cervical Cancer Classification from Pap Smear Images using Deep Convolutional Neural Network Models,” Interdisciplinary Sciences: Computational Life Sciences, https://doi.org/10.1007/s12539-023-00589-5

190. Lin Sun, Mengmeng Li, Weiping Ding,  Jiucheng Xu, “Adaptive Fuzzy Multi-neighborhood Feature Selection with Hybrid Sampling and Its Application for Class-imbalanced Data,” Applied Soft Computing, https://doi.org/10.1016/j.asoc.2023.110968

191. Jicun Jiang, Xiaodi Liu, Zengwen Wang, Weiping Ding, Shitao Zhang,  “Large group emergency decision-making with bi-directional trust in social networks: A probabilistic hesitant fuzzy integrated cloud approach,”  Information Fusion, 102 (2024) 102062.  https://doi.org/ 10.1016/j.inffus.2023.102062.  

192. Xianfeng Huang, Jianming Zhan, Weiping Ding, Witold Pedrycz, “Regret theory-based multivariate fusion prediction system and its application to interest rate estimation in multi-scale information systems,” Information Fusion 2023,99:101860. https://doi.org/10.1016/j.inffus.2023.101860  

193. Bin Zhu, Meng Wu, Yunpeng Hong, Yi Chen, Bo Xie, Fei Liu, Chenyang Bu, Weiping Ding, “MMIEA: Multi-modal Interaction Entity Alignment Model for Knowledge Graph,”  Information Fusion, 100 (2023) 101935. https://doi.org/10.1016/j.inffus.2023.101935  

194. Wenqian Shang, Jiazhao Chai, Jianxiang Cao, Xia Lei, Haibin Zhu, Yongkai Fan, Weiping Ding,“Aspect-level Sentiment Analysis Based on Aspect-Sentence Graph Convolution Network,” Information Fusion ，104 (2024) 102143.  https://doi.org/10.1016/j.inffus.2023.102143   

195. Zhuoxin He, Yaojin Lin, Chenxi Wang, Lei Guo, Jinkun Chen,  Weiping Ding, “Multi-Label Feature Selection Based on Correlation Label Enhancement,” Information Sciences  647(2023) 119526. https://doi.org/10.1016/j.ins.2023.119526  

196. Zhen-Song Chen, Zhuo-Ran Wang , Muhammet Deveci ,Weiping Ding, Witold Pedrycz, Miroslaw J. Skibniewski, “Optimization-based probabilistic decision support for assessing building information modelling maturity considering multiple objectives ,” Information Fusion, 102 (2024) 102026. https://doi.org/10.1016/j.inffus.2023.102026   

197. Pingxin Wang, Xibei Yang, Weiping Ding, Jianmin Zhan, Yiyu Yao, “Three-way clustering: Foundations, Survey and Challenges,” Applied Soft Computing  151 (2024) 111131 https://doi.org/10.1016/j.asoc.2023.111131

198. Huchang Liao, Jiaxin Qi, Jiawei Zhang, Chonghui Zhang, Fan Liu, Weiping Ding, “Mining and fusing unstructured online reviews and structured public index data for hospital selection, ”Information Fusion,103 (2024) 102142. https://doi.org/10.1016/j.inffus.2023.102142  

199. Lin Sun, Yuxuan Ma, Weiping Ding, Jiucheng Xu, “SFSLH: Sparse Feature Selection via Local Feature and High-order Label Correlation,” Applied Intelligence, https://doi.org/10.1007 /s10489-023-05136-9

200. Ya’nan Guan, Weiping Ding, Shujiao Liao, Wenyuan Yang,” CycMixer: A simplified and rapidly converging object detection network of query based on cycle mixing,” Engineering Applications of Artificial Intelligence ,127 (2024) 107220 https://doi.org/10.1016/ j.engappai.2023.107220

201. Hassan A. Alsattar, Sarah Qahtan, Nahia Mourad, A.A. Zaidan, Muhammet Deveci, Weiping Ding, “Three-Way Decisions based Conditional Probabilities by Opinion Scores and Bayesian Rules in Circular-Pythagorean Fuzzy Sets for Developing Sustainable Smart Living Framework,”Information Sciences  649 (2023) 119681. https://doi.org/10.1016/j.ins.2023.119681  

202. Benjamín Gutierrez-Serafín, Javier Andreu-Perez, Humberto Pérez-Espinosa, Silke Paulmann; Weiping Ding,” Toward assessment of human voice biomarkers of brain lesions through explainable deep learning,” Biomedical Signal Processing and Control 87 (2024) 105457.https://doi.org/10.1016/j.bspc.2023.105457

203. Wenbin Qian, Fankang Xua, Jin Qian, Wenhao Shu, Weiping Ding, “Multi-label Feature Selection based on Rough Granular-Ball and Label Distribution,” Information Sciences,650 (2023) 119698. https://doi.org/10.1016/j.ins.2023.119698  

204. Chuanbin Zhang, Long Chen, Zhaoyin Shi and Weiping Ding, “Latent Information-Guided One-Step Multi-View Fuzzy Clustering Based on Cross-View Anchor Graph,” Information Fusion 102 (2024) 102025. https://doi.org/10.1016/j.inffus.2023.102025  

205. Yingbai Hu , Xu Wang , Yueyue Liu, Weiping Ding, and Alois Knoll,  “PI-ELM: Reinforcement Learning-based Adaptable Policy Improvement for Dynamical System,” Information Sciences  650 (2023) 119700.  https://doi.org/10.1016/j.ins.2023.119700  

206. Yan Tian, Zhaocheng Xu, Yujun Ma, Weiping Ding, Ruili Wang, Zhihong Gao, Guohua Cheng, Linyang He, Xuran Zhao, “Survey on Deep Learning in Multimodal Medical Imaging for Cancer Detection,” Neural Computing and Applications,https://doi.org/10.1007/s00521-023-09214-4

207. Lin Sun, Shanshan Si, Weiping Ding,   Xinya Wang, Jiucheng Xu, “ Multiobjective Sparrow Search Feature Selection with Sparrow Ranking and Preference Information and Its Applications for High-Dimensional Data,” Applied Soft Computing, https://doi.org/10.1016/j.asoc.2023.11083

208. Di Jin, Luzhi Wang, He Zhang,  Yizhen Zheng, Weiping Ding,  Feng Xia, Shirui Pan,”A Survey on Fairness-aware Recommender Systems,” Information Fusion 100 (2023) 101906. https://doi.org/10.1016/j.inffus.2023.101906  

209. Ke Wang, Zicong Chen, Xilin Dang, Xuan Fan, Xuming Han, Chien-Ming Chen, WeiPing Ding, Siu-Ming Yiu, “Uncovering Hidden Vulnerabilities in Convolutional Neural Networks through Graph-based Adversarial Robustness Evaluation,” Pattern Recognition  (2023), doi: https://doi.org/10.1016/j.patcog.2023.109745

210. Muhammad Anwar Ma’sum, Mahardhika Pratama, Edwin Lughofer, Weiping Ding, Wisnu Jatmiko,  “Assessor-guided learning for continual environments,” Information Sciences 640 (2023) 119088. https://doi.org/10.1016/j.ins.2023.119088   

211. Hebing Nie, Qun Wu, Haifeng Zhao, Weiping Ding, Muhammet Devec, “Flexible Adaptive Graph Embedding for Semi-supervised Dimension Reduction,” Information Fusion,  DOI: 10.1016/j.inffus.2023.101872  

212. Doudou Guo, Weihua Xu, Yuhua Qian, Weiping Ding, “M-FCCL: Memory-based concept-cognitive learning for dynamic fuzzy data classification and knowledge fusion,” Information Fusion，https://doi.org/10.1016/j.inffus.2023.101962  

213. Yaozu Wu, Yankai Chen, Zhishuai Yin, Weiping Ding, and Irwin King, “A Survey on Graph Embedding Techniques for Biomedical Data:Methods and Applications,”  Information Fusion 100 (2023) 101909. https://doi.org/10.1016/j.inffus.2023.101909  

214. Xiaobo Li, Qiyong Fu, Qi Li,  Weiping Ding, Feilong Lin, Zhonglong Zheng, “Multi-Objective Binary Grey Wolf Optimization for Feature Selection Based on Guided Mutation Strategy,”  Applied Soft Computing  145 (2023) 110558. https://doi.org/10.1016/j.asoc.2023.110558

215. Zuowei Zhang, Liangbo Ning, Zechao Liu, Qingyu Yang, Weiping Ding, “Mining and Reasoning of Data Uncertainty-induced Imprecision in Deep Image Classification” Information Fusion,  96 (2023) 202–213. DOI: https://doi.org/10.1016/j.inffus. 2023.03.014  .

216. Qinghua Zhang, Ying Yang, Yunlong Chen, Guoyin Wang, Weiping Ding, Weizhi Wu, Weizhi Danilo Pelusi “Information fusion for multi-scale data: Survey and challenges,” Information Fusion,100 (2023) 101954,  doi: https://doi.org/10.1016/j.inffus.2023.101954  

217. Wenbin Qian, Jintao Huang, Fankang Xu, Wenhao Shu, Weiping Ding, ”A Survey on Multi-label Feature Selection from Perspectives of Label Fusion,” Information Fusion  (2023), doi: https://doi.org/10.1016/j.inffus.2023.101948  .

218. Erfan Babaee Tirkolaee, Ali Ebadi Torkayesh, Madjid Tavana, Alireza Goli, Vladimir Simic, Weiping Ding, “An Intelligent Decision Support System for Resilient-Reliable Supply Chain Network Design,”  Engineering Applications of Artificial Intelligence 126 (2023) 106945 https://doi.org/10.1016/j.engappai.2023.106945

219. Jianghui Sang, Yongli Wang, Weiping Ding, Zaki Ahmad Khan, Lin Xu,” Reward Shaping with Hierarchical Graph Topology”, Pattern Recognition 143 (2023) 109746. https://doi.org/10.1016/j.patcog.2023.109746

220. Marek Moleda, Bożena Małysiak-Mrozek, Weiping Ding,  Vaidy Sunderam, Dariusz Mrozek*, “From corrective to predictive maintenance - a review of maintenance approaches for the power industry,”  Sensor, 2023, 23, 5970. https://doi.org/10.3390/s23135970

221. Pengyu Xue, Liguo Fei, Weiping Ding, “A volunteer allocation optimization model in response to major natura disasters based on improved Dempster-Shafer theory,” Expert Systems with Applications, 236 (2024) 121285. https://doi.org/10.1016/j.eswa.2023.121285

222. Zuhe Li, Qingbing Guo,Yushan Pan, Weiping Ding, Jun Yu,Yazhou Zhang,Weihua Liu,Haoran Chen, Hao Wang,Ying Xie, “Multi-level Correlation Mining Framework with Self-supervised Label Generation for Multimodal Sentiment Analysis,” Information Fusion，99 (2023) 101891 https://doi.org/10.1016/j.inffus.2023.101891  

223. Xunjin Wu, Jianming Zhan,  Weiping Ding, “ TWC-EL: A multivariate prediction model by the fusion of three-way clustering and ensemble learning,”  Information Fusion,100 (2023) 101966, https://doi.org/10.1016/j.inffus.2023.101966  

224. Xianfeng Huang, Jianming Zhan, Weiping Ding, Witold Pedrycz, “Regret theory-based multivariate fusion prediction system and its application to interest rate estimation in multi-scale information systems,” Information Fusion , 99 (2023) 101860. https://doi.org/10.1016/j.inffus.2023.101860  

225. Deepak Kumar Jain, Shamimul Qamar, Saurabh Raj Sangwan, Weiping Ding, Anand J Kulkarni, “Ontology-Based Natural Language Processing for Sentimental Knowledge Analysis Using Deep Learning Architectures,” ACM Transactions on Asian and Low-Resource Language Information Processing, https://doi.org/10.1145/3624012

226. Priti Bansal, Vincenzo Piuri, Vasile Palade, Weiping Ding, “Topical Collection on Deep Learning in Multimodal Medical Imaging for Cancer Detection” Neural Computing and Applications, https://doi.org/10.1007/s00521-023-08955-6

227.  Weiping Ding, Jun Liu,Chin‐Teng Lin, Dariusz Mrozek, “Special issue on Recent Advances in Fuzzy Deep Learning for Uncertain Medicine Data,” Information Sciences DOI: https://doi.org/10.1016/j.ins.2023.118997  .

228. Tian Xie, Weiping Ding, Jinbao Zhang , Xusen Wan and Jiehua Wang, “Bi-LS-AttM: A Bidirectional LSTM and Attention Mechanism Model for Improving Image Captioning,” Applied Sciences 2023, 13, 7916. https://doi.org/10.3390/app13137916

229. Di Jin, Luzhi Wang, He Zhang,  Yizhen Zheng, Weiping Ding, Feng Xia, Shirui Pan,”A Survey on Fairness-aware Recommender Systems,” Information Fusion 100 (2023) 101906. https://doi.org/10.1016/j.inffus.2023.101906  

230. Yecong Wan, Mingwen Shao,Yuanshuo Cheng, Weiping Ding, “Fuzzy-based Cross-Image Pixel Contrastive Learning for Compact Medical Image Segmentation,” Multimedia Tools and Application, https://doi.org/10.1007/s11042-023-16611-3

231. Weijie Xu, Lina Nie, Beijing Chen, and Weiping Ding, “Dual-stream EfficientNet with Adversarial Sample Augmentation for COVID-19 Computer Aided Diagnosis,” Computers in Biology and Medicine,165 (2023) 107451. https://doi.org/10.1016/j.compbiomed.2023.107451

232. Zhengxin Song, Yun Xue, Donghong Gu, Haolan Zhang, Weiping Ding, “Target oriented multimodal sentiment classifcation by using topic model and gating mechanism”, International Journal of Machine Learning and Cybernetics, https://doi.org/10.1007/ s13042-022-01757-7

233. Cong Huang, Peng Mei, Quan Shi and Serdar Coskun, Weiping Ding, “State-Saturated Resilient Filtering for Nonlinear Complex Networks Under Event-Triggering Protocol,” Asian Journal of Control , 2023, 25(2):1216-1231 http://dx.doi.org/10.1002/asjc.2906

234. Md. Milon Islam, Md. Zabirul Islam, Amanullah Asraf,  Weiping Ding, “Diagnosis of COVID-19 from X-rays Using Combined CNN-RNN Architecture with Transfer Learning” BenchCouncil Transactions on Benchmarks, Standards and Evaluations，2 (2022) 100088, https://doi.org/10.1016/j.tbench.2023.100088

235. Rongtao Zhang, Xueling Ma, Weiping Ding, Jianming Zhan, “MAP-FCRNN: Multi-step ahead prediction model using forecasting correction and RNN model with memory functions,”Information Sciences, 646 (2023) 119382. https://doi.org/10.1016/j.ins.2023.119382  

236. Weiping Ding, Mohamed Abdel-Basset, Reda Mohamed, “HAR-DeepConvLG: Hybrid Deep Learning–based Model for Human Activity Recognition in IoT Applications,” Information Sciences , 646 (2023) 119394. https://doi.org/10.1016/j.ins.2023.119394  

237. Xiaobo Li, Qiyong Fu, Qi Li, Weiping Ding, Feilong Lin, Zhonglong Zheng, “Multi-Objective Binary Grey Wolf Optimization for Feature Selection Based on Guided Mutation Strategy,”  Applied Soft Computing,  145 (2023) 110558. https://doi.org/10.1016/j.asoc.2023.110558

238. Marek Moleda, Bożena Małysiak-Mrozek, Weiping Ding, Vaidy Sunderam, Dariusz Mrozek, “From corrective to predictive maintenance -A review of maintenance approaches for the power industry,”  Sensor , 2023, 23, 5970. https://doi.org/10.3390/s23135970

239. Anubha Parashar, Apoorva Parashar, Weiping Ding, Mohammad Shabaz, Imad Rida, “Data Preprocessing and Feature Selection Techniques in Gait Recognition: A Comparative Study of Machine Learning and Deep Learning Approaches,” Pattern Recognition Letters, 172 (2023) 65–73. DOI: https://doi.org/10.1016/j.patrec.2023.05.021

240. Hangming Zhang, Hanping Hu, Weiping Ding, “HSVCML: Image encryption algorithm based on Hilbert sorting vector and new spatiotemporal chaotic system,” Optics and Laser Technology,  167 (2023) 109655. DOI:https://doi.org/10.1016/j.optlastec.2023.109655 

241. Lin Sun, Shujing Sun,  Weiping Ding,  Xinyue Huang, Peiyi Fan, Kunyu Li, Leqi Chen, “Feature Selection Using Symmetric Uncertainty and Hybrid Optimization for High-dimensional Data”  International Journal of Machine Learning and Cybernetics,  DOI:  https://doi.org/10.1007/s13042-023-01897-4 

242. Jianghui Sang, Yongli Wang, Weiping Ding,  Zaki Ahmad Khan, Lin Xu,” Reward Shaping with Hierarchical Graph Topology”, Pattern Recognition 143 (2023) 109746. https://doi.org/10.1016/j.patcog.2023.109746 

243. Lin Sun, Shujing Sun, Weiping Ding,  Xinyue Huang, Peiyi Fan, Kunyu Li, Leqi Chen, “Feature Selection Using Symmetric Uncertainty and Hybrid Optimization for High-dimensional Data”  International Journal of Machine Learning and Cybernetics,DOI:  https://doi.org/10.1007 /s13042-023-01897-4

244. Weiping Ding, Xinjie Shen, Jiashuang Huang, Hengrong Ju, Yuepeng Cheng, Tao Yin, “Brain age prediction based on resting-state functional MRI using similarity metric convolutional neural network,” IEEE ACCESS, DOI: 10.1109/ACCESS.2023.3283148

245. Hengrong Ju, Weiping Ding, Xibei Yang, and Pingping Gu “Bi-directional adaptive neighborhood rough sets based attribute subset selection,” International Journal of Approximate Reasoning，https://doi.org/10.1016/j.ijar.2023.108966 

246. Dexuan Xu, Huashi Zhu, Yu Huang, Zhi Jin, Weiping Ding, Hang Li, Menglong Ran,  “Vision-knowledge fusion model for multi-domain medical report generation, ” Information Fusion, 97 (2023) 101817 https://doi.org/10.1016/j.inffus.2023.101817  .

247. Tengbiao Li, Junsheng Qiao, Weiping Ding, “Three-way conflict analysis and resolution based on q-rung orthopair fuzzy information,” Information Sciences 638 (2023) 118959  https://doi.org/10.1016/j.ins.2023.118959  .

248. Zhaoyi Yuan, Hao Ding, Guoqing Chao, Mingqiang Song, Lei Wang, Weiping Ding, Dianhui Chu, “A Diabetes Prediction System Based on Incomplete Fused Data Sources” Machine Learning and Knowledge Extraction, 2023, 5, 384–399. https://doi.org/10.3390/make5020023.

249. Aparna Pramanik, Asit Kumar Das, Weiping Ding,  “Graph based fuzzy clustering algorithm for crime report labelling,” Applied Soft Comptuing  141 (2023) 110261  https://doi.org/10.1016/j.asoc.2023.110261.

250. Lin Sun, Yusheng Chen, Weiping Ding, Jiucheng Xu, “LEFSA: Label Enhancement-based Feature Selection with Adaptive Neighborhood via Ant Colony Optimization for Multilabel Classification,” International Journal of Machine Learning and Cybernetics, DOI:10.1007/s13042-023-01924-4 

251. Sarah Qahtan, Aws Alaa Zaidan, Hassan Abdulsattar Ibrahim, Muhammet Deveci, Weiping Ding, Dragan Pamucar,” A decision modeling approach for smart training environment with motor Imagery-based brain computer interface under neutrosophic cubic fuzzy set,” Expert Systems With Applications, 224 (2023) 119991

252. Lin Sun, Yusheng Chen, Weiping Ding, Jiucheng Xu, Yuanyuan Ma “AMFSA: Adaptive Fuzzy Neighborhood-Based Multilabel Feature Selection with Ant Colony Optimization," Applied Soft Computing  138 (2023) 110211. https://doi.org/10.1016/j.asoc.2023.110211

253. Cong Huang, Quan Shi, Weiping Ding, Ling Liu and Shu Jiang, “A Robust MPC Approach for Platooning Control of Automated Vehicles With Constraints on Acceleration,” Control Engineering Practice(2023) https://doi.org/10.1016/j.conengprac.2023.105648 

254. Chenglong Zhu, Xueling Ma, Chao Zhang, Weiping Ding, Jianming Zhan,” Information granules-based long-term forecasting of time series via BPNN under three-way decision framework,” Information Sciences 634 (2023) 696–715, https://doi.org/10.1016/j.ins.2023.03.133  

255. Xiangbin Liu, Shufen Hou, Shuai Liu,  Weiping Ding, Yudong Zhang,”Attention-based Multimodal Glioma Segmentation with Multi-attention Layers for Small-intensity Dissimilarity,” Journal of King Saud University - Computer and Information Sciences, https://doi.org/10.1016/ j.jksuci.2023.03.011

256. Yinxin Bao, JiaLi Liu, Qinqin Shen, Yang Cao,  Weiping Ding, Quan Shi, “PKET-GCN: Prior Knowledge Enhanced Time-Varying Graph Convolution Network for Traffic Flow Prediction” Information Sciences    634 (2023) 359-381. https://doi.org/10.1016/j.ins.2023.03.093  

257. Mu Nie, Zhibin Quan, Weiping Ding, Wankou Yang, “Enhancing Motion Visual Cues for Self-supervised Video Representation Learning” Engineering Applications of Artificial Intelligence, 123 (2023) 106203. https://doi.org/10.1016/j.engappai.2023.106203

258. Cong Huang, Weiping Ding,  Ruifeng Gao, Peng Mei and Hamidreza Karimi, “Distributed State-of-Charge Estimation for Lithium-Ion Batteries With Random Sensor Failure Under Dynamic Event-Triggering Protocol,”  Information Fusion  95 (2023) 293–305 https://doi.org/10.1016/ j.inffus. 2023.02.032

259. Weiping Ding, Mohamed Abdel-Basset, Reda Mohamed, “DeepAK-IoT: An Effective Deep Learning Model for cyberattack detection in IoT networks”  Information Sciences, 634 (2023) 157-171. https://doi.org/10.1016/j.ins.2023.03.052  

260. Weiping Ding, Mohamed Abdel-Basset, Hossam Hawash, Sara Abdel-Razek, and Chuansheng Liu, “Fed-ESD: Federated Learning for Efficient Epileptic Seizure Detection in the Fog-Assisted Internet of Medical Things,” Information Sciences， 630 (2023) 403–419  DOI: https://doi.org/10.1016/j.ins.2023.02.052  

261. Cong Huang, Weiping Ding, Ruifeng Gao, Peng Mei and Hamidreza Karimi, “Distributed State-of-Charge Estimation for Lithium-Ion Batteries With Random Sensor Failure Under Dynamic Event-Triggering Protocol,”  Information Fusion，95 (2023) 293–305 https://doi.org/10.1016 /j.inffus.2023.02.032

262. Yinxin Bao, Jiashuang Huang, Qinqin Shen, Yang Cao, Weiping Ding, Zhenquan Shi, Quan Shi,"Spatial-Temporal Complex Graph Convolution Network for Traffic Flow Prediction,”Engineering Applications of Artificial Intelligence, 121 (2023) 106044. https://doi.org/ 10.1016/j.engappai.2023.106044   

263. Lin Sun, Xinya Wang, Weiping Ding, Jiucheng Xu, “TFSFB: Two-stage Feature Selection via Fusing Fuzzy Multi-neighborhood Rough Set with Binary Whale Optimization for Imbalanced Data ”  Information Fusion 95 (2023) 91–108. https://doi.org/10.1016/j.inffus.2023.02.016   

264. Anubha Parashar, Apoorva Parashar,Weiping Ding,  Rajveer S Shekhawat and Imad Rida,“Deep Learning Pipelines for Recognition of Gait Biometrics with Covariates - A Comprehensive Review,” Artificial Intelligence Review (2023) https://doi.org/10.1007/s10462-022-10365-4 

265. Xuewei Li, Jinming Ma, Jian Yu, Mankun Zhao, Mei Yu, Hongwei Liu, Weiping Ding, Ruiguo Yu,“A Structure-Enhanced Generative Adversarial Network for Knowledge Graph Zero-Shot Relational Learning, ” Information Science, 2023, 629: 169–183. https://doi.org/10.1016/j.ins.2023  . 01.113

266. Lin Sun, Shanshan Si, Weiping Ding,  Jiucheng Xu, Yan Zhang，“BSSFS: Binary Sparrow Search Algorithm for Feature Selection,” International Journal of Machine Learning and Cybernetics.   DOI : 10.1007/s13042-023-01788-8.

267. Deepak Kumar Jain, Weiping Ding,Ketan Kotech, “Training Fuzzy Deep Neural Network with Honey Badger Algorithm for Intrusion Detection in Cloud Environment,”  International Journal of Machine Learning and Cybernetics，doi.10.1007/s13042-022-01758-6.

268. Weiping Ding, Mohamed Abdel-Basset, Nour Mostafa, Hossam Hawash “Interval type-2 Fuzzy Temporal Convolutional Autoencoder for Gait-Based Human Identification and Authentication,” Information Sciences, 2022,597: 144-165. doi:10.1016/j.ins. 2022.03.046  

269. Yuanpeng Zhang, Guanjin Wang, Xiuyu Huang, Weiping Ding, “TSK fuzzy system fusion at sensitivity-ensemble-level for imbalanced data classification,” Information Fusion, 92 (2023) 350–362.doi:10.1016/j.inffus.2022.12.014.  

270. Wenbin Qian, Yihui Li, Qianzhi Ye, Weiping Ding, Wenhao Shu, “Disambiguation-based Partial Label Feature Selection via Feature Dependency and Label Consistency,”   Information Fusion, 94 (2023) 152–168  https://doi.org/10.1016/j.inffus.2023.01.019.  

271. Yuanpeng Zhang, Weiping Ding, “Motor Imagery Classification Via Stacking-based Takagi-Sugeno-Kang Fuzzy Classifier Ensemble” Knowledge-Based Systems, 263 (2023) 110292.

272. doi:10.1016/j.knosys.2023.110292.

273. Weiping Zhang, Mohit Kumar, Weiping Ding, Xiujuan Li, Junfeng Yu, “Variational Learning of Deep Fuzzy Theoretic Nonparametric Model," Neurocomputing, 506 (2022) 128–145. doi: 10.1016/j.neucom.2022.07.029.    

274. Anubha Parashar, Apoorva Parashar, Weiping Ding, Rajveer S Shekhawat and Imad Rida,“Deep Learning Pipelines for Recognition of Gait Biometrics with Covariates - A Comprehensive Review,” Artificial Intelligence Review, https://doi.org/10.1007/s10462-022-10365-4.

275. Changzhong Wang, Xiang Lv, Xiaodong Fan,  Weiping Ding, and Xiaoli Jiang, “Two-channel Deep Recursive Multi-Scale Network Based on Multi-Attention for No-reference Image Quality Assessment,” International Journal of Machine Learning and Cybernetics，https://doi.org/10.1007/s13042-023-01773-1.

276. Pengfei Shi, Li Guo, Chenglizhao Chen, Long Chen and Weiping Ding,  “Pixel and Region Level Information Fusion in Membership Regularized Fuzzy Clustering for Image Segmentation,”  Information Fusion, 92 (2023) 479–497. doi:10.1016/j.inffus.2022.12.008.  

277. Gholamreza Haseli, Ramin Ranjbarzadeh, Mostafa Hajiaghaei-Keshteli, Saeid Jafarzadeh Ghoushchi, Aliakbar Hasani, Muhammet Deveci, Weiping Ding,  “HECON: Weight Assessment of the Product Loyalty Criteria Considering the Customer Decision's Halo Effect Using the Convolutional Neural Networks,” Information Sciences,  623 (2023) 184–205 . doi: 10.1016 /j.ins.2022.12.027.

278. Nezir Aydin, Sukran Seker, Muhammet Deveci, Weiping Ding,  Dursun Delen, “A Linear Programming-based QFD Methodology under Fuzzy Environment to Develop Sustainable Policies in Apparel Retailing Industry,” Journal of Cleaner Production, 387 (2023) 135887.

279.     doi: 10.1016/j.jclepro.2023.135887.

280. Jinghua Liu, Yaojin Lin, Weiping Ding,  Hongbo Zhang, Cheng Wang, Jixiang Du, “Multi-label feature selection based on label distribution and neighborhood rough set,”  Neurocomouting  524 (2023) 142–157. doi:10.1016/j.neucom.2022.11.096.  

281. K. Venkatachalam, Pavel Trojovsk, Nebojsa Bacanin, Muhammet Deveci, Weiping Ding, “Bimodal HAR-An Efficient Approach to Human Activity Analysis and Recognition Using Bimodal Hybrid Classifiers,”  Information Sciences, https://doi.org/10.1016/j.ins.2023.01.121   

282. Weiping Ding, Mohamed Abdel-Basset, Hossam Hawash, and Ahmed M. Ali , “Explainability of Artificial Intelligence Methods, Applications and Challenges: A Comprehensive Survey,” Information Sciences, 615 (2022) 238–292. https://doi.org/10.1016/j.ins.2022.10.013  

283. Weiping Ding, Yurui Ming, Yu-Kai Wang, Chin-Teng Lin, “Memory augmented convolutional neural network and its application in bioimages,” Neurocomputing，2021,466:128-138. doi: 10.1016/j.neucom. 2021.09.012  .

284. Weiping Ding, Jiandong Wang, and Jiehua Wang, “Multigranulation Consensus Fuzzy-Rough based Attribute Reduction,” Knowledge-Based Systems, 2020,198, 105945. doi:10.1016 /j.knosys.2020.105945.

285. Weiping Ding, Chin-Teng Lin, Alan Wee-Chung Liew, Isaac Triguero, and WenjianLuo, “Current trends of granular data mining for biomedical data analysis,” Information Sciences, 2020, 510: 341-343. doi: 10.1016/j.ins. 2019.10.002  .

286. Weiping Ding, Janmenjoy Nayak, H. Swapnarekha, Ajith Abraham, Bighnaraj Naik, and Danilo Pelusi, “Fusion of Intelligent Learning for COVID-19: A State-of-the-Art Review and Analysis on Real Medical Data,” Neurocomputing, 2021,457: 40-66. doi:10.1016/ j.neucom.2021.06.024.

287. Chun Cheng, Yun Luo, Chang-bin Yu and Weiping Ding, “Social bots and mass media manipulate public opinion through dual opinion climate,” Chinese Physics B, 2022, 31 (1): 018701. DOI: 10.1088/1674-1056/ac0baa

288. Cong Huang, Peng Mei, Quan Shi, Serdar Coskun, Weiping Ding, “State-Saturated Resilient Filtering for Nonlinear Complex Networks Under Event-Triggering Protocol,” Asian Journal of Control, DOI:http://doi.org/10.1002/asjc.2906

289. Shuang An, Mengru Zhang, Changzhong Wang, Weiping Ding, “Robust Fuzzy Rough Approximations with kNN Granules for Semi-Supervised Feature Selection,”   Fuzzy Sets and Systems, DOI: https://doi.org/10.1016/j.fss.2023.01.01.

290. Ganeshsree Selvachandran, Shio Gai Quek, Raveendran Paramesran, Weiping Ding,  Le Hoang Son, “Developments in the Detection of Diabetic Retinopathy: A State of the Art Review of Computer-Aided Diagnosis and Machine Learning Methods,” Artificial Intelligence Review, 2023, 56, pp. 915–964, http://dx.doi.org/10.1007/s10462-022-10185-6.

291. Weiping Ding, Chin-Teng Lin, Senbo Chen, Xiaofeng Zhang, Bin Hu, “Multiagent-Consensus- MapReduce-Based attribute reduction using co-evolutionary quantum PSO for big data applications,” Neurocomputing, 2018, 272: 136-153. doi:10.1016/ j.neucom.2017.06.059.

292. Weiping Ding, Chin-Teng Lin, Mukesh Prasad, “Hierarchical co-evolutionary clustering tree-based rough feature game equilibrium selection and its application in neonatal cerebral cortex MRI,” Expert Systems with Application, 2018, 101, 243-257. doi:10.1016/j.eswa.2018.01.053.

293. Weiping Ding, Jiehua Wang, and Jiandong Wang, “A hierarchical-coevolutionary-MapReduce- based knowledge reduction algorithm with robust ensemble Pareto equilibrium,” Information Sciences, 2016, 342: 153-175. doi:10.1016/ j.ins. 2016. 01.035.

294. Weiping Ding, Zhijin Guan, Quan Shi, and Jiandong Wang, “A more efficient attribute self-adaptive co-evolutionary reduction algorithm by combining quantum elitist frogs and cloud model operators,” Information Sciences, 2015, 293: 214-234. doi:10.1016/j.ins.2014.09.010.  

295. Weiping Ding, Zhihao Feng, Javier Andreu-Perez, and Witold Pedrycz, “A Derived Multi-population Genetic Algorithm For Adaptive Fuzzy C-Means Clustering,” Neural Processing Letters, DOI: 10.1007/s11063-022-10876-9.

296. Weiping Ding, Tingzhen Qin, Xinjie Shen, Hengrong Ju, Haipeng Wang, Jiashuang Huang, Ming Li, “Parallel incremental efficient attribute reduction algorithm based on attribute tree,”Information Sciences, 610 (2022) 1102–1121. https://doi.org/10.1016/j.ins  . 2022.08.044

297. Weiping Ding, Mohamed Abdel-Basset, Hossam Hawash, and Witold Pedrycz, “MIC-Net: A Deep Network for Cross-site Segmentation of COVID-19 Infection in the Fog-assisted IoMT,” Information Sciences 623 (2023) 20–39   https://doi.org/10.1016/j.ins.2022.12.017  .

298. Hengrong Ju, Weiping Ding,  Zhenquan Shi, Jiashuang Huang, Jie Yang, Xibei Yang, “Attribute reduction with personalized information granularity of nearest mutual neighbors”,  Information Sciences 613 (2022) 114–138.https://doi.org/10.1016/j.ins.2022.09.006  .

299. Weiping Ding,  Javier Andreu Perez, Yiu-ming Cheung, Swagatam Das, Xiaodong Yue, Dariusz Mrozek, “Special issue on fuzzy systems for biomedical science in healthcare,” Applied Soft Computing 132 (2023) 109834. doi: https://doi.org/10.1016/j.asoc.2022.109834.

300. Gholamreza Haseli, Ramin Ranjbarzadeh, Mostafa Hajiaghaei-Keshteli, Saeid Jafarzadeh Ghoushchi, Aliakbar Hasani, Muhammet Deveci, Weiping Ding, “HECON: Weight Assessment of the Product Loyalty Criteria Considering the Customer Decision's Halo Effect Using the Convolutional Neural Networks,” Information Sciences   https://doi.org/10.1016/j. ins.2022.12.027

301. Jiashuang Huang, Mingliang Wang, Weiping Ding, Daoqiang Zhang, “SD-CNN: A Static-Dynamic Convolutional Neural Network for Functional Brain Networks,” Medical Image Analysis 83 (2023) 102679. https://doi.org/10.1016/j.media.2022.102679.

302. Sankhadeep Chatterjee, Soumyajit Maity, Mayukh Bhattacharjee, Soumen Banerjee, Asit Kumar Das, Weiping Ding, “Variational Autoencoder based Imbalanced COVID-19 detection using chest X-Ray Images,” New Generation Computing, https://doi.org/10.1007/s00354-022-00194-y.

303. Jiang Deng, Jianming Zhan, Weiping Ding, Peide Liu, Witold Pedrycz, “A novel prospect-theory-based three-way decision methodology in multi-scale information systems ” Artificial Intelligence Review , https://doi.org/10.1007/s10462-022-10339-6.

304. Jianying Chen, Yun Xue, Haolan Zhang, Weiping Ding, Zhengxuan Zhang, Jiehai Chen, “On development of multimodal named entity recognition using part of speech and mixture of experts”, International Journal of Machine Learning and Cybernetics, https://doi.org/ 10.1007/s13042-022-01754-w

305. Guoqing Chao, Xingquan Zhu, Weiping Ding, Jinbo Bi, Shiliang Sun, “Editorial: special issue on multi-view learning,” Applied Intelligence，https://doi.org/10.1007/s10489-022-03650-w.

306. Lin Sun, Mengmeng Li, Weiping Ding, En Zhang, Xiaoxia Mu, Jiucheng Xu, “AFNFS: Adaptive Fuzzy Neighborhood-Based Feature Selection with Adaptive Synthetic Over-sampling for Imbalanced Data,” Information Sciences, https://doi.org/10.1016/j.ins  . 2022.08.118

307. Peng Ping, Cong Huang,  Weiping Ding, Miyajima Chiyomi, Yongkang Liu and Takeda Kazuya, “Distracted Driving Detection Based on the Fusion of Deep Learning and Casual Reasoning”   Information Fusion 89 (2023) 121-142.DOI: https://doi.org/10.1016/j.inffus  . 2022.08.009.

308. Ilgın Gokasar, Dragan Pamucar, Muhammet Deveci, Weiping Ding, “A Novel Rough Numbers based Extended MACBETH Method Implementation in the Prioritization of the Connected Autonomous Vehicles,” Expert Systems With Applications, 211 (2023) 118445. https://doi.org/10.1016/j.eswa.2022.118445  .

309. Rong Jiang, Xue Chen, Yimin Yu, Ying Zhang, Weiping Ding,  “An Access Control Model for Medical Big Data Based on Clustering and Risk,” Information Sciences, 621 (2023) 691–707 doi: https://doi.org/10.1016/j.ins.2022.11.102  .

310. Şükran Şeker, Fatma Betül Bağlan, Nezir Aydin, Muhammet Deveci, Weiping Ding,  “ Risk Assessment Approach for Analyzing Risk Factors to Overcome Pandemic Using Interval-Valued Q-rung Orthopair Fuzzy Decision Making Method,”  Applied Soft Computing,132 (2023) 109891, doi: https://doi.org/10.1016/j.asoc.2022.109891  .

311. Sarah Qahtan, Hasan A. Alsattar, A.A. Zaidan, Muhammet Deveci, Dragan Pamucar, Weiping Ding,  “A Novel Fuel Supply System Modelling Approaches for Electric Vehicles Under Pythagorean Probabilistic Hesitant Fuzzy Sets,”  Information Sciences 622 (2023) 1014–1032. doi:https://doi.org/10.1016/j.ins.2022.11.166  .

312. Yufei Chen, Chang Xu, Weiping Ding, Shichen Sun, Xiaodong Yue，Hamido Fujita, “Target-Aware U-Net with Fuzzy Skip Connections for Refined Pancreas Segmentation” Applied Soft Computing  131 (2022) 109818  https://doi.org/10.1016/j.asoc.2022.109818.

313. Lin Sun, Xinya Wang, Weiping Ding, Jiucheng Xu, “TSFNFS: Two-Stage-Fuzzy-Neighborhood Feature Selection with Binary Whale Optimization Algorithm,” International Journal of Machine Learning and Cybernetics  , DOI:10.1007/s13042-022-01653-0

314. Lin Sun, Xinya Wang, Weiping Ding, Jiucheng Xu, “TSFNFR: Two-Stage Fuzzy Neighborhood-based Feature Reduction with Binary Whale Optimization Algorithm for Imbalanced Data Classification,” Knowledge-Based Systems, 256 (2022) 109849.  DOI: https://doi.org /10.1016/j.knosys.2022.109849

315. Lin Sun, Tianxiang Wang, Weiping Ding, Jiucheng Xu,Anhui Tan,“Two-Stage-Neighborhood-Based Multilabel Classification for Incomplete Data with Missing Labels,” International Journal of Intelligent Systems，  https://doi.org/10.1002/int.22861  .

316. Renyan Feng, Erman Acar, Yisong Wang, Wanwei Liu, Stefan Schlobach, Weiping Ding, “Computing Sufficient and Necessary Conditions in CTL: A Forgetting Approach,” Information Sciences, https://doi.org/10.1016/j.ins.2022.10.124  

317. Lei Dai, Liming Zhang, Zehua Chen, Weiping Ding, “Collaborative Granular Sieving: A Deterministic Multi-evolutionary Algorithm for Multimodal Optimization Problems” Information Sciences, 613 (2022) 288–308. https://doi.org/10.1016/j.ins.2022.09.007  

318. Beijing Chen, Tianmu Li, and Weiping Ding, “Detecting Deepfake Videos Based on Spatiotemporal Attention and Convolutional LSTM,” Information Sciences,  601 (2022) 58–70. DOI:10.1016/j.ins.2022.04.014.   

319. Xiaoyan Zhang, Xiuwei Chen, Weihua Xu, and Weiping Ding, “Dynamic Information Fusion in Multi-Source Incomplete Interval-Valued Information System with Variation of Information Sources and Attributes,” Information Sciences 608 (2022) 1–27  https://doi.org/10.1016/j. ins.2022.06.054 

320. Weiping Ding, Javier Andreu Perez, Yiu-ming Cheung, Swagatam Das, Xiaodong Yue, Dariusz Mrozek, “Special issue on fuzzy systems for biomedical science in healthcare,” Applied Soft Computing (2022), doi: https://doi.org/10.1016/j.asoc.2022.109834.

321. Ganeshsree Selvachandran, Shio Gai Quek, Raveendran Paramesran, Weiping Ding,  Le Hoang Son, “Developments in the Detection of Diabetic Retinopathy: A State of the Art Review of Computer-Aided Diagnosis and Machine Learning Methods,” Artificial Intelligence Review，https://doi.org/10.1007/s10462-022-10185-6. 

322. Jinxin Cao, Weizhong Xu, Di Jin, Dongxiao He, Xiaofeng Zhang, and Weiping Ding, “A Network Embedding-Enhanced NMF Methods for Finding Communities in Attributed Networks” IEEE ACCESS, DOI: 10.1109/ACCESS.2022.3198979.

323. Weiping Ding, Bairu Pan, Hengrong Ju, Jiashuang Huang, Chun Cheng, Xinjie Shen, Yu Geng, Tao Hou,” RG-GCN: Improved graph convolution neural network algorithm based on Rough Graph,”IEEE ACCESS, 2022.10, 85582-85594. doi:10.1109/ACCESS.2022. 3198730.

324. Xianfeng Huang, Jianming Zhan, Weiping Ding, Witold Pedrycz, ”An error correction prediction model based on three-way decision and ensemble learning,”  International Journal of approximate reasoning ，146 (2022) 21–46. doi:10.1016/j.ijar.2022.04.002. 

325. Qinting Jiang, Xuanhong Zhou, Ruili Wang, Weiping Ding, Yi Chu, Sizhe Tang, Xiaoyun Jia, Xiaolong Xu, “Intelligent Monitoring for Infectious Diseases with Fuzzy Systems and Edge Computing:  A Survey” Applied Soft Computing, 123 (2022) 108835. https://doi.org/10.1016 /j.asoc.2022.108835. 

326. Wenjie Wang, Jianming Zhan, Weiping Ding, Shuping Wan，“A three-way decision method with tolerance dominance relations in decision information systems,”   Artificial Intelligence Review, Accepted and to be appeared

327. Changzhong Wang, Xiang Lv, Weiping Ding, Xiaodong Fan, “No-reference image quality assessment with multi-scale weighted residuals and channel attention mechanism,” Soft Computing, https://doi.org/10.1007/s00500-022-07535-5  .

328. Weizhong Wang, Xiao Han,  Weiping Ding, Qun Wu, Xiaoqing Chen, Muhammet Deveci, “A Fermatean Fuzzy Fine-Kinney for Occupational Risk Evaluation Using Extensible MARCOS with Prospect Theory,”  Engineering Applications of Artificial Intelligence,117 (2023) 105518 https://doi.org/10.1016/j.engappai.2022.105518

329. Anubha Parashar, Rajveer Singh Shekhawat, Weiping Ding, Imad Rida, “Intra-class variations with Deep Learning-based Gait Analysis: A comprehensive survey of covariates and methods, ” Neurocomputing, 505 (2022) 315–338. https://doi.org/10.1016/j.neucom  . 2022.07.002

330. Zhe Wang, Fuyuan Xiao, and Weiping Ding, “Interval-Valued Intuitionistic Fuzzy Jenson-Shannon Divergence and its application in Multi-Attribute Decision Making,” Applied Intelligence,  https://doi.org/10.1007/s10489-022-03347-0

331. Jiandong Kuang, Ming-Wen Shao, Ran Wang, Wangmeng Zuo, Weiping Ding, “Network Pruning via Probing the Importance of Filters,” International Journal of Machine Learning and Cybernetics， https://doi.org/10.1007/s13042-022-01530-w   

332. Chongsheng Zhang, Paolo Soda, Jingjun Bi, Gaojuan Fan, George Almpanidis, Salvador Garc and Weiping Ding, “An Empirical Study on the Joint Impact of Feature Selection and Data Resampling on Imbalance Classification,” Applied Intelligence , 2022.  DOI: 10.1007/s10489-022-03772-1.

333. Supriyo Ahmed, Ripon K. Chakrabortty, Daryl L. Essam, Weiping Ding“Poly-linear Regression with Augmented Long Short Term Memory Neural Network: Predicting Time Series Data” Information Sciences, 606 (2022) 573–600. https://doi.org/10.1016/j.ins.2022.05.078  

334. Felin Wilta, Allyson Li Chen Chong, Ganeshsree Selvachandran, Ketan Kotecha, Weiping Ding,  “Generalized Susceptible-Exposed-Infectious-Recovered Model and its Contributing Factors for Analyzing the Death and Recovery Rates of the COVID-19 Pandemic,” Applied Soft Computing,123(2022) 108973. https://doi.org/10.1016/j.asoc.2022.108973

335. Dixizi Liu, Weiping Ding,  Zhijie Sasha Dong, and Witold Pedrycz “Optimizing Deep Neutral Networks to Predict the Effect of Social Distancing on COVID-19 Spread,” Computers & Industrial Engineering,  166 (2022) 107970, dio:10.1016/j.cie.2022.107970.

336. Lin Sun, Tianxiang Wang, Weiping Ding,  Jiucheng Xu,Anhui Tan,“Two-Stage-Neighborhood-Based Multilabel Classification for Incomplete Data with Missing Labels,” International Journal of Intelligent Systems, DOI:10.1002/int.22861  .

337. Weiping Ding, and Jiandong Wang, “A novel approach to minimum attribute reduction based on quantum-inspired self-adaptive cooperative co-evolution,” Knowledge-Based Systems, 2013, 50: 1-13.  dio:10.1016/ j.knosys.2013.03.008.

338. Jiahao Huang, Weiping Ding, Jun Lv, Jingwen Yang, Hao Dong, Javier Del Ser, Jun Xia, Tiaojuan Ren, Stephen T. Wong, Guang Yang, “Edge-Enhanced Dual Discriminator Generative Adversarial Network for Fast MRI with Parallel Imaging Using Multi-view Information,” Applied Intelligence, https://doi.org/10.1007/s10489-021-03092-w 

339. Lin Sun, Jiuxiao Zhang,  Weiping Ding, Jiucheng Xu, “Mixed Measure-Based Feature Selection Using the Fisher Score and Neighborhood Rough Sets,” Applied Intelligence, DOI:10.1007/s10489-021-03142-3.

340. Lin Sun, Jiuxiao Zhang,  Weiping Ding, Jiucheng Xu, “Feature Reduction for Imbalanced Data Classification Using Similarity-based Feature Clustering and Adaptive Weighted K-Nearest Neighbors,”  Information Sciences, 593 (2022) 591–613. DOI: 10.1016/j.ins.2022.02.004.   

341. Fuyuan Xiao, and Weiping Ding, “Divergence measure of Pythagorean fuzzy sets and its application in medical diagnosis,” Applied Soft Computing, 2019, 79, 254-267. doi:10.1016/j.asoc.2019.03.043. (Highly Cited Paper) 

342. Huijing Ma, Qinghao Ye, Weiping Ding, Yinghui Jiang, Minhao Wang, Zhangming Niu, Xi Zhou, Yuan Gao, Chengjia Wang, Wade Menpes-Smith, Evandro F. Fang, Jianbo Shao, Jun Xia, Guang Yang*, “Can Clinical Symptoms and Laboratory Results Predict CT Abnormality? Initial Findings Using Novel Machine Learning Techniques in Children with COVID-19 Infections” Frontiers in Oncology, DOI:10.3389/fmed.2021.699984.

343. Dongxiao He, Youyou Wang, Jinxin Cao, Weiping Ding,  Shizhan Chen, Zhiyong Feng,  Bo Wang, Yuxiao Huang, "A Network Embedding-Enhanced Bayesian Model for Generalized Community Detection in Complex Networks," Information Sciences, 575 (2021) 306-322. doi:10.1016/j. ins.2021.06.020.

344. Christian Flores Vega, Jonathan Quevedo, Elmer Escand´on, Mehrin Kiani, Weiping Ding, Javier Andreu-Perez, “Fuzzy Temporal Convolutional Neural Networks in P300-based Brain-Computer Interface for Smart Home Interaction”, Applied Soft Computing, 117 (2022) 108359. DOI:10.1016/j.asoc.2021.10835 

345. Jin Ye, Jianming Zhan, Weiping Ding,  Hamido Fujita, “A novel three-way decision approach in decision information systems,”  Information Sciences, 584 (2022) 1–30. DOI: 10.1016/j.ins. 2021.10.042    (Highly Cited Paper)

346. Michail Mamalakis, Andrew J. Swift, Bart Vorselaars, Surajit Ray, Simonne Weeks, Weiping Ding, Richard H. Clayton,Louise S. Mackenzie, Abhirup Banerjee, “DenResCov-19: A transfer deep-learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays,”  Computerized Medical Imaging and Graphics，94 (2021) 102008，DOI:10.1016/j.compmedimag.2021.102008

347. Ying Li, Binbin Fan, Weiping Ding,  Weiping Zhang, Jianwei Yin, “A Novel Severity Calibration Algorithm for Defect Detection by Constructing Maps,” Information Sciences. https://doi.org/10.1016/j.ins.2022.06.076.  

348. Ying Li, Binbin Fan,Weiping Zhang, Weiping Ding, Jianwei Yin, “Deep Active Learning for Object Detection,” Information Sciences, 579 (2021) 418–433.  doi: 10.1016/j.ins.2021.08.0  19

349. Lin Sun, Xiaoying Qin, Weiping Ding, and Jiucheng Xu, “Nearest Neighbors-based Adaptive Density Peaks Clustering with Optimized Allocation Strategy,” Neurocomputing，doi:10.1016/j.neucom.2021.12.019   

350. Lin Sun, Tianxiang Wang, Weiping Ding, Jiucheng Xu, Yaojin Lin, “Feature Selection Using Fisher-Score and Multilabel Neighborhood Rough Sets for Multilabel Classification,” Information Sciences, 578 (2021) 887–912. doi: 10.1016/j.ins.2021.08.0  32

351. Kehua Yuan, Weihua Xu, Wentao Li, Weiping Ding, “An incremental learning mechanism for object classification based on progressive fuzzy three-way concept,”  Information Sciences, 584 (2022) 127–147. DOI:10.1016/j.ins. 2021.10.058  

352. Kun Zhu, Shi Ying, Weiping Ding, Nana Zhang and Dandan Zhu, “IVKMP：A robust data-driven heterogeneous defect model based on deep representation optimization learning” Information Sciences, 583 (2022) 332–363. DOI: 10.1016/j.ins. 2021.  11.029. 

353. Weiping Ding,  Janmenjoy Nayak, H. Swapnarekha, Ajith Abraham, Bighnaraj Naik, and Danilo Pelusi, “Fusion of Intelligent Learning for COVID-19: A State-of-the-Art Review and Analysis on Real Medical Data,” Neurocomputing,  457 (2021) 40-66. doi:10.1016/j.neucom.2021.06.024.  

354. Weiping Ding,  Mohamed Abdel-Basset, Hossam Hawash, “RCTE: A Reliable and Consistent Temporal-Ensembling Framework for Semi-supervised Segmentation of COVID-19 Lesion,“  Information Sciences, 578 (2021) 559-573. DOI: 10.1016/j.ins.2021.07.059  .  

355. Xiuyi Jia, Tao Wen, Weiping Ding,  Huaxiong Li, Weiwei Li, “Semi-supervised Label Distribution Learning via Projection Graph Embedding,” Information Sciences，581 (2021) 840–855. doi: 10.1016/j.ins.2021.10.009.  

356. Lin Sun, Xiaoying Qin, Weiping Ding, Jiucheng Xu, Shiguang Zhang, “Density Peaks Clustering Based on k-nearest neighbors and Self-Recommendation,”  International Journal of Machine Learning and Cybernetics, 2021,12: 1913-1938.

357. Linyao Yang, Xiao Wang, Yuxin Dai, Kejun Xin, Xiaolong Zheng, Weiping Ding, Jun Zhang and Fei-Yue Wang, “HackRL: Reinforcement Learning with Hierarchical Attention for Cross-Graph Knowledge Fusion and Collaborative Reasoning,”  Knowledge-Based Systems, 233 (2021) 107498.

358. Yintong Wang, Yingjie Yang, Weiping Ding, Shuo Li, “A residual-attention offline handwritten Chinese text recognition based on fully convolutional neural networks,”  IEEE Access, DOI: 10.1109/ACCESS.2021.3115606.

359. Tao Yin, Xiaojuan Mao, Xingtan Wua, Hengrong Ju, Weiping Ding and Xibei Yang,”An improved D-S evidence theory based neighborhood rough classification approach,” Journal of Intelligent & Fuzzy Systems, DOI:10.3233/JIFS-210462.

360. Qinghao Ye, Yuan Gao, Weiping Ding, Zhangming Niu, Chengjia Wang, Yinghui Jiang, Minhao Wang, Evandro  Fei Fang, Wade Menpes-Smith, Jun Xia, and Guang Yang,“Robust Weakly Supervised Learning for COVID-19 Recognition Using Multi-Center CT Images,” Applied Soft Computing, 116 (2022) 108291  doi: 10.1016/j.asoc. 2021.108291.

361. Amit Saxena, Mukesh Prasad, Akshansh Gupta, Neha Bharill, Om Prakash Patel, Aruna Tiwari, Meng Joo Er, Weiping Ding, and Chin-Teng Lin, “A review of clustering techniques and developments,” Neurocomputing, 2017, 267: 664-681. doi:10.1016/ j.neucom.2017.06.053. (Highly Cited Paper) 

362. Shuai Liu, Dongye Liu, Khan Muhammad, and Weiping Ding, “Effective Template Update Mechanism in Visual Tracking with Background Clutter," Neurocomputing,  458(2021) 615-625. doi:10.1016/j.neucom. 2019.12. 143  .  (Highly Cited Paper)

363. Beijing Chen, Xingwang Ju, Bin Xiao, Weiping Ding*, Yuhui Zheng, and Victor Hugo C. de Albuquerque, “Locally GAN-generated face detection based on an improved Xception,”  Information Sciences, 2021. doi:10.1016/j.ins. 2021.05.  006.

364. Weiping Ding, Yi Zhang, Tingzhen Qin, Ying Sun, “An improved SFLA-Kmeans algorithm based on approximate backbone and its application in retinal fundus image,” IEEE Access，2021,9:72259-72268.  DOI: 10.1109/ ACCESS.2021.3079119.

365. Chien-Ming Chen, Lili Chen, Wensheng Gan, Lina Qiu, and Weiping Ding, “Discovering High Utility-Occupancy Patterns from Uncertain Data,” Information Sciences, 2021, 546: 1208-1229. doi: 10.1016/j.ins.2020.10.001.  

366. Nana Zhang, Shi Ying, Weiping Ding, Kun Zhu, Dandan Zhu, “WGNCS: A robust hybrid cross-version defect model via multi-objective optimization and deep enhanced feature representation” Information Sciences,  doi: 10.1016/j.ins.2021.05.008.  

367. Changzhong Wang, Yang Huang, Weiping Ding,  and Zehong Cao, “Attribute reduction with fuzzy rough self-information measures,” Information Sciences,  2021, 549: 68-86. doi: 10.1016/j.ins.2020.11.021  .(Highly Cited Paper)

368. Chirantana Mallick, Asit Kumar Das, Weiping Ding, and Janmenjoy Nayak，"Ensemble Summarization of Bio-medical Articles integrating Clustering and multi-objective Evolutionary Algorithms,"  Applied Soft Computing, 106 (2021) 107347. doi:10.1016/j.asoc.2021.107347.

369. Hengrong Ju, Weiping Ding, Xibei Yang, Hamido Fujitac, Suping Xu, ”Robust supervised rough granular description model with the principle of justifiable granularity”  Applied Soft Computing, 2021, 110: 107612.  DOI: 10.1016/j.asoc.2021. 107612

370. Erfan Babaee Tirkolaee, Mahdi Alinaghian, Zahra Kaviani Dezaki, Seyyed Reza Hejazi, Weiping Ding, “An Augmented Tabu Search Algorithm for the Green Inventory-Routing Problem with Time Windows,” Swarm and Evolutionary Computation, 60 (2021) 100802. doi: 10.1016/j.swevo.2020.100802.  (Highly Cited Paper)

371. Fei Xiong, Yu Zheng, Weiping Ding, Hao Wang, Xinyi Wang, Hongshu Chen, “Control Strategy in Spreading Dynamics with Limited Capacity,” Future Generation Computer Systems, 114 (2021) 307-317. doi: 10.1016/j.future.2020.08.009.

372. Tanveer Hussain, Khan Muhammad, Weiping Ding, Mohsen Guizani, and Sung Wook Baik, Vector Hugo C. de Albuquerque. “A Comprehensive Survey on Multi-View Video Summarization,” Pattern Recognition, doi: 10.1016/j.patcog.2020.107567.

373. Jiahui Chen, Xu Guo, Wensheng Gan, Chien-Ming Chen, Weiping Ding,  “On-Shelf Utility Mining from Transaction Database,” Engineering Applications of Artificial Intelligence, 107 (2022) 104516. DOI:10.1016/j.engappai. 2021.104516.

374. Priyanka Das, Asit Kumar Das, Janmenjoy Nayak, Danilo Pelusi and Weiping Ding, “Incremental Classifier in Crime Prediction using bi-objective Particle Swarm Optimization,” Information Sciences, 2021, 56: 279-303. doi: 10.1016/ j.ins.2021.02.002.

375. Amin Ullah, Khan Muhammad, Weiping Ding, Vasile Palade, Ijaz Ul Haq, and Sung Wook Baik, “Efficient Activity Recognition using Lightweight CNN and Deep GRU Network for Surveillance Applications,” Applied Soft Computing, 103 (2021) 107102, doi:10.1016/j.asoc.2021.107102

376. Janmenjoy Nayak, Bighnaraj Naik, Paidi Dinesh, Kanithi Vakula, B. Kameswara Rao, Weiping Ding, and Danilo Pelusi, “Intelligent System for Covid-19 Prognosis: A State-of-the-Art Survey" Applied Intelligence, （2021）51:2908-2938. doi:10.1007/s10489-020-02102-7

377. Lin Sun, Tengyu Yin, Weiping Ding, Yuhua Qian, and Jiucheng Xu, “Multilabel Feature Selection Using ML-ReliefF and Neighborhood Mutual Information for Multilabel Neighborhood Decision Systems,” Information Sciences, 537 (2020) 401–424, doi: 10.1016/j. ins. 2020.05.102.

378. Weiping Ding, Gary G. Yen, Gleb Beliakov, Isaac Triguero, Mahardhika Pratama, Xiangliang Zhang, and Hongjun Li, “Editorial: Data Mining and Granular Computing in Big Data and Knowledge Processing,” IEEE Access, 2019, 7(1): 47682-47686. doi:10.1109/ACCESS. 2019.2908776.

379. Mohamed Abdel-Basset, Weiping Ding, and Doaa El-Shahat, “An Hybrid Harris Hawks Optimization Algorithm with simulated annealing for Feature Selection,” Artificial Intelligence Review. 2021,54(1): 593-637. doi:10. 1007/s10462-020-09860-3.

380. Weiping Ding, Ying Sun, Longjie Ren, Hengrong Ju, Zhihao Feng, and Ming Li, “Multiple Lesions Detection of Fundus Images based on Convolution Neural Network Algorithm with Improved SFLA,” IEEE Access, 2020, 8: 97618-97630. doi: 10.1109/ACCESS. 2020.2996569.

381. Mohamed Abdel-Basset, Weiping Ding, and Laila Abdel-Fatah, “The fusion of Internet of Intelligent Things (IoIT) in Remote Diagnosis of Obstructive Sleep Apnea: A Survey & A New Model,” Information Fusion, 61 (2020) 84–100. doi:10.1016 /j.inffus. 2020.03.010.

382. Ghazaala Yasmin, Asit Kumar Das, Janmenjoy Nayak, Danilo Pelusi and Weiping Ding, “Graph based Feature Selection Investigating Boundary Region of Rough Set for Language Identification,” Expert Systems With Applications, doi:10.1016/ j.eswa.2020.113575.

383. Qingyong Wang, Yun Zhou, Weiping Ding, Zhiguo Zhang, Khan Muhammad, and Zehong Cao, “Random Forest with Self-paced Bootstrap Learning in Lung Cancer Prognosis,” ACM Transactions on Multimedia Computing Communications and Applications, 16, 1s, Article 34 (April 2020), 12 pages. https://doi.org/10.1145/3345314.

384. Wenjian Luo, Nannan Lu, Li Ni, Wenjie Zhu, and Weiping Ding, “Local Community Detection by the Nearest Nodes with Greater Centrality,” Information Sciences, 2020, 517: 377–392. doi: 10.1016/j.ins.2020.01.001.  

385. Lin Sun, Lanying Wang, Weiping Ding, Yuhua Qian, and Jiucheng Xu, “Neighborhood Multi-granulation Rough Sets-based Attribute Reduction Using Lebesgue and Entropy Measures in Incomplete Neighborhood Decision Systems,” Knowledge-Based Systems, 192 (2020) 105373. doi:10.1016/j.knosys.2019.105373.

386. Lin Sun, Tengyu Yin, Weiping Ding, and Jiucheng Xu, “Hybrid Multilabel Feature Selection Using BPSO and Neighborhood Rough Sets for Multilabel Neighborhood Decision Systems,” IEEE Access, 2019,7(1):175793-175815. dio:10.1109 /ACCESS.2019.2957662

387. Zhi Dou, Lin Sun, and Weiping Ding, “Multiple parameters determination for image and video deconvolution using genetic algorithm and generalized Stein's unbiased risk estimation,” IEEE Access,  2019, 7 (1): 177745-177760. doi:10.1109/ ACCESS.2019.2958315.

388. V.D.Ambeth Kumar, S.Malathi, R Venkatesan, K Ramalakshmi, K Vengatesan  and Weiping Ding, K. Abhishek, “Exploration of an innovative geometric parameter based on performance enhancement for foot print recognition,” Journal of Intelligent & Fuzzy Systems,  2020, 38(2): 2181-2196. doi: 10.3233/JIFS-190982. 

389. Priyanka Das, Asit Kumar Das, Janmenjoy Nayak, Danilo Pelusi and Weiping Ding, “Group Incremental Adaptive Clustering based on Neural Network and Rough Set Theory for Crime Report Categorization,” Neurocomputing. 459 (2021) 465–480. doi:10.1016/j.neucom. 2019.10. 109.  

390. Qi Li, Zehong Cao, Weiping Ding, and Qing Li, “A Multi-Objective Adaptive Evolutionary Algorithm to Extract Communities in Networks,” Swarm and Evolutionary Computation, 52 (2020) 100629. doi:10.1016/ j.swevo.2019.100629.

391. Santos Kumar Baliarsingh, Weiping Ding, Swati Vipsita, and Sambit Bakshi, “A Memetic Algorithm using Emperor Penguin and Social Engineering Optimization for Medical Data Classification,” Applied Soft Computing, 2019, 85, 105773. doi: 10.1016/j.asoc. 2019.105773.

392. Weiping Ding, “SVM-Based Feature Selection for Differential Space Fusion and Its Application to Diabetic Fundus Image Classification,” IEEE Access, 2019,7: 149493-149502. doi: 10.1109/ACCESS.2019.2944899.

393. Yurui Ming, Weiping Ding, Danilo Pelusi, Dongrui Wu, Yu-Kai Wang, Mukesh Prasad, and Chin-Teng Ling, “Subject Adaptation Network for EEG Data Analysis,” Applied Soft Computing, 84 (2019) 105689. doi:10.1016/j.asoc. 2019.105689.

394. Xiaowei Gu, and Weiping Ding, “A Hierarchical Prototype-Based Approach for Classification,” Information Sciences, 2019, 505, 325–351. doi: 10.1016/j.ins.2019.07.077  .

395. Md. Milon Islam, Md. Zabirul Islam, Amanullah Asraf, and Weiping Ding, “Diagnosis of COVID-19 from X-rays Using Combined CNN-RNN Architecture with Transfer Learning,”  medRxiv preprint, https://doi.org/10.1101/ 2020.08.24. 20181339.

396. Shiming Chen, Wenjie Wang, Beihao Xia, Xinge You, Qinmu Peng, Zehong Cao, and Weiping Ding, ”CDE-GAN: Cooperative Dual Evolution Based Generative Adversarial Network,” arXiv:2008.09388v1[cs.CV] 21 Aug 2020.

397. Priyanka Das, Asit Kumar Das, Janmenjoy Nayak, Danilo Pelusi, and Weiping Ding, “A Graph based Clustering Approach for Relation Extraction from Crime Data,” IEEE Access, 2019, 7, 101269-101282. doi:10.1109/ACCESS. 2019.2929597.

398. Chin-Teng Lin, Juang-Tai King, Priyanka Bhardwaj, Chih-Hao Chen, Akshansh Gupta, Weiping Ding, and Mukesh Prasad, “EOG-based Eye Movement Classification and Application on HCI Baseball Game,” IEEE Access, 2019, 7(1): 96166-96176. doi:10.1109/ACCESS. 2019.2927755.

399. Linbo Wang, Hui Zhen, Xianyong Fang, Shaohua Wan, Weiping Ding, and Yanwen Guo, “A Unified Two-Parallel-Branches Deep Neural Network for Joint Gland Contour and Segmentation Learning,” Future Generation Computer Systems, 2019, 100, 316-324. doi: 10.1016/j.future. 2019.05.035.

400. Chin-Teng Lin, Jung-Tai King, Chun-Hsiang Chuang, Weiping Ding, Wei-Yu Chuang, Lun-De Liao, and Yu-Kai Wang, “Exploring the Brain Responses to Driving Fatigue through Simultaneous EEG and fNIRS Measurements,” International Journal of Neural Systems, 30(1): 1950018:1-1950018:12 (2020). doi:10.1142/ S01290657195 00187.

401. Zongyuan Zhang, Zhijin Guan, Hong Zhang, Haiying Ma, and Weiping Ding, “A method for synthesis and optimization for linear nearest neighbor quantum circuits by parallel processing,” Quantum Information & Computation, 18(13&14): 1095-1114 (2018).

402. Swagatika Devi, Manmath Narayan Sahoo,  Khan Muhammad, Weiping Ding, and Sambit Bakshi, “Hiding Medical Information in Brain MR Images without Affecting Accuracy of Classifying Pathological Brain,” Future Generation Computer Systems, 2019, 99: 235-246. doi:10.1016/j.future.2019.01.047.

403. Hengrong Ju, Witold Pedrycz, Huaxiong Li, Weiping Ding, and Xibei Yang, “Sequential three-way classifier with justifiable granularity,” Knowledge-Based Systems, 2019, 163: 103–119. doi:10.1016/j.knosys.2018.08.022.

404. Akshansh Gupta, Ramesh Kumar Agrawal, Jyoti Singh Kirar, Baljeet Kaur, Weiping Ding,  Chin-Teng Lin, Andreu Perez Javier, and Mukesh Prasad, “A Hierarchical Meta-model for Multi-Class Mental Task Based Brain-Computer Interfaces,” Neurcomputing, 389 (2020) 207–217. doi:10.1016/j.neucom.2018.07.094.  

405. Zehong Cao, Weiping Ding, Yu-Kai Wang, Farookh Khadeer Hussain, Adel Al-Jumaily, and Chin-Teng Lin, “Effects of repetitive SSVEPs on EEG complexity using inherent fuzzy entropy,” Neurcomputing, 389 (2020) 198–206. doi: 10.1016/ j.neucom.2018.08.091. (Highly Cited Paper) 

406. Shiming chen, Yisong Wang, Chin-Teng Lin, Weiping Ding, and Zehong Cao, “Semi-supervised feature learning for improving writer identification,” Information Sciences, 482 (2019) 156-170.  doi:10.1016/j.ins.2019.01.024.  

407. Xueyun Cheng, Zhijin Guan, and Weiping Ding, “Mapping from multiple control Toffoli circuits to linear nearest neighbor quantum circuits,” Quantum Information Processing, 2018 2018, 17(7):169, July. doi: 10.1007/s11128-018-1908-8.

408. Zongyuan Zhang, Zhijin Guan, Hong Zhang, Haiying Ma, and Weiping Ding, “A method for synthesis and optimization for linear nearest neighbor quantum circuits by parallel processing,” Quantum Information & Computation, 18(13&14): 1095-1114 (2018).

409. Ziyun Deng, Tingqin He, Weiping Ding, and Zehong Cao, “A Multi-Model Fusion Engine for Filtering Web Pages,” IEEE Access, 2018, 6: 66062–66071. doi: 10.1109/ACCESS. 2018.2878897.

410. Tao Meng, Lijun Cai, Tingqin He, Lei Chen, Ziyun Deng, Weiping Ding, and Zehong Cao, “A Modified Distance Dynamics Model for Improvement of Community Detection,” IEEE Access, 2018, 6: 63934-63947. doi:10.1109/ ACCESS.2018.2877235.

411. Guoqing Chao, Yuan Luo, and Weiping Ding, “Recent advances in supervised dimension reduction:  A survey,” Machine Learning and Knowledge Extraction, 2019, 1(1), 341–358. doi:10.3390/make1010020 (Invited Survey)

412. Weiping Ding, Zhijin Guan, Jiehua Wang, and Di Tian, “A layered co-evolution based rough feature selection using adaptive neighborhood radius hierarchy and its application in 3D-MRI,” Chinese Journal of Electronics, 2017, 26(6): 1168-1176. doi:10.1049/cje.2017.01.004.

413. Weiping Ding, Jiandong Wang, Yuehua Li, and Xueyun Cheng, “A cascaded co-evolutionary model for attribute reduction and classification based on coordinating architecture with bidirectional elitist optimization,” Chinese Journal of Electronics, 2017, 26(1): 13-21. doi:10.1049/cje.2016. 06.037.

414. Weiping Ding, Zhijin Guan, and Quan Shi, “An enhanced attribute co-evolutionary game reduction algorithm by integrating self-adaptive multi-level Nash equilibrium,” Chinese Journal of Electronics, 2016, 25(1): 13-19. doi:10.1049/ cje.2016.01.003.

415. Weiping Ding, and Jiandong Wang, “Ensemble feature selection integrating elitist roles based quantum game algorithm,” Journal of Systems Engineering and Electronics, 2015, 26(3), 584-594. doi:10.1109/JSEE.2015.0006.

416. Weiping Ding, Jiandong Wang, and Zhijin Guan, “A novel minimum attribute reduction algorithm based on hierarchical elitist role model combining competitive and cooperative co-evolution,” Chinese Journal of Electronics, 2013, 22(4): 677-682.

417. Weiping Ding, Jiandong Wang, Zhijin Guan, and Quan Shi, “Enhanced minimum attribute reduction based on quantum-inspired shuffled frog leaping algorithm,” Journal of Systems Engineering and Electronics, 2013, 24(3): 426-434. doi:10.1109/ JSEE.2013.00051.

418. Weiping Ding, Jiandong Wang, and Zhijing Guan, “Cooperative extended rough attribute reduction algorithm based on improved PSO,” Journal of Systems Engineering and Electronics,  2012, 23(1): 160-166.  doi:10.1109/ JSEE.2012.00020.

419. Weiping Ding, Jiandong Wang, and Yanwen Guo, “Minimum attribute co-reduction algorithm based on multilevel evolutionary tree with self-adaptive subpopulations,” Transactions of Nanjing University of Aeronautics & Astronautics, 2013, 30(2): 175-184.

420. Weiping Ding, and Jiandong Wang, “Quantum-cloud-feedback-based attribute equilibrium dominance ensemble reduction with co-evolutionary elitists,” Journal of Quantum Electronics, 2016, 33 (2): 220-230. doi:10.3969/ j.issn.1007-5461.2016. 02.15  

421. Xueyun Chen, Zhijin Guan, Weiping Ding, and Pengcheng Zhu, “Linear nearest neighbor quantum circuit synthesis based on valid Boolean matrix,” Journal of Quantum Electronics, 2016, 33(6) 743-750.

422. Weiping Ding, Jiandong Wang, Quan Shi, and Zhijin Guan, “Adaptive multicascade attribute reduction based on quantum-inspired mixed co-evolution,” Journal of Southeast University (English Edition), 2012, 28(2): 145-150.

423. Weiping Ding, Wang Jiandong, Zhang Xiaofeng, and Guan Zhijin, “Co-evolutionary cloud-based attribute ensemble multi-agent reduction algorithm,” Journal of Southeast University (English Edition), 2016, 32(4):432-438. doi:10.3969/ j.issn.1003-7985.2016.04.007.

424. Weiping Ding, Jiandong Wang, Quan Shi, Senbo Chen, and Xuehua Sen, “Attribute equilibrium reduction with quantum game based on mixed co-evolutionary populations’ collaboration,” ACTA ELECTRONICA SINICA, 2015, 43(1): 45-53. doi:10.3969/j.issn.0372-2112.2005.01008.

425. Weiping Ding, Jiandong Wang, and Zhijin Guan, “Minimum attribute self-adaptive cooperative co-evolutionary reduction algorithm based on quantum elitist frogs,” Journal of Computer Research and Development, 2014, 51(4): 743-753. doi:10.7544/issn1000-1239. 2014.20120572.

426. Weiping Ding, Jiandong Wang, Zhijin Guan, and Quan Shi, “Minimum attribute reduction enhancing algorithm based on quantum cloud model evolution,” Journal of Southeast University (Natural Science), 2013, 43(2): 291-295.

427. Weiping Ding, Jiandong Wang, and Zhijin Guan, “Efficient rough attribute reduction based on quantum frog co-evolution,” ACTA ELECTRONICA SINICA, 2011, 39(11): 2597-2603.

428. Weiping Ding, Jiandong Wang, Senbo Chen, Xueyun Cheng, and Xuehua Sen, “Rough attribute reduction with cross-entropy based on improved shuffled frog-leaping algorithm,” Journal of Nanjing University (Natural Science), 2015, 50(2): 159-166. 

429. Weiping Ding, Jiandong Wang, Quan Shi, Hao Zhu, and Senbo Chen, “Attribute order reduct algorithm based on niche technology and perfect attribute-value space tree,” Journal of Nanjing University of Science and Technology (Natural Science), 2012, 36 (1): 37-42. 

430. Weiping Ding, Jiandong Wang, Zhijin Guan, and Quan Shi, “A cascade algorithm of quantum evolutionary attribute reduction and classification learning based adaptive crossover cooperation,” Pattern Recognition and Artificial Intelligence, 2011, 24(6): 733-742. 

431. Weiping Ding, and Jiandong Wang, “Incomplete attribute reduction robust algorithm of decision table based niche conic neighborhood particle swarm optimization,” Journal of Sichuan University (Engineering Science Edition), 2011, 43(6): 119- 126.

432. Weiping Ding, Jiandong Wang, and Zhijin Guan. ”Concept lattice mining algorithm using rough entropy with variable precision thresholding and co-evolution,” Journal of PLA University of Science and Technology, 2011, 12(1): 25-30.  

433. Weiping Ding, Jiandong Wang, Weihua Duan, and Quan Shi, "Research of cooperative PSO for attribute reduction optimization," Journal of Shangdong University (Natural Science), 2011, 46 (5): 97-102. 

434. Weiping Ding, Jiandong Wang, and Weihua Duan, “Research and application of extension rough formal concept mining algorithm based on dynamic co-evolution,” Journal of Information and Computational Science, 2010,7(12): 2377-2384. 

435. Weiping Ding, Jiandong Wang, Hao Zhu, Zhijin Guan, and Quan Shi, “A novel hybrid approach for incomplete knowledge system mining based on approximation rough entropy lattice,” Journal of Computational Information System, 2010, 6(5): 1651-1659.

436. Weiping Ding, Jiandong Wang, Zhijin Guan, and Hao Zhu, "The algorithm of attribute reduction based on extension entropy of variable precision thresholding in incomplete information system," Journal of Chinese Computer Systems, 2010, 31(12): 2372-2376.

437. Weiping Ding, Jiandong Wang, Hao Zhu, Zhijin Guan, and Quan Shi, "Research and application of dynamical classification model for ensemble learning based on approximation concept lattice of roughness," Computer Science, 2010, 37(7): 174-178, 232.

438. Weiping Ding, Zhijin Guan, and Zhenguo Shi, “Research of approximation concept lattice and rules mining based on extended rough sets model,” Journal of Nanjing University of Posts and Telecommunications (Natural Science), 2009, 29(2): 10-15.

Selected Conferences Papers

1. Zhihao Feng, Weiping Ding, Jinxin Cao, Chudi Sun, Xinjie Shen, Haipeng Wang, “Adaptive FCM Clustering Algorithm Based On Twin Multiple Population Evolution,”  2021 IEEE International Conference on Digital Twins and Parallel Intelligence (DTPI 2021) Beijing, China, July 15-August 15, pp.434-437, 2021. DOI: 10.1109/DTPI52967.2021.9540159

2. Peng Ping,  Weiping Ding, Yongkang Liu, and Kazuya Takeda，“An enhanced driver's risk perception modeling based on gate recurrent unit network,” 2022 33rd IEEE Intelligent Vehicles Symposium(IV)(IV 2022), June 5-9,2022, in Aachen, Genmany. 

3. Xinjie Shen, Jiashuang Huang, Ying Sun, Ming Li, Bairu Pan, Weiping Ding, “Parallel Pathway Convolutional Neural Network with Low-rank Fusion for Brain Age Prediction,” 2021 IEEE International Conference on Digital Twins and Parallel Intelligence (DTPI 2021) Beijing, China, July 15-August 15, pp.434-437, 2021. DOI: 10.1109/DTPI52967.2021.9540107

4. Chien-Ming Chen, Lili Chen, Wensheng Gan, Lina Qiu, Weiping Ding, “UHUOPM: High Utility Occupancy Pattern Mining in Uncertain Data” 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)，October 11, 2020, pp.3066-3071.

5. Mahardhika Pratama, Choiru Zain, Andri Ashfahani, Yew-Soon Ong and Weiping Ding, “Automatic Construction of Multi-layer Perceptron Network from Streaming Examples,” The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), November 2019 Pages 1171–1180. https://doi.org/10.1145/3357384.3357946.

6. Jiahui Chen, Xu Guo, Wensheng Gan, Chien-Ming Chen, Weiping Ding, and Guoting Chen,"OSUMI: On-Shelf Utility Mining from Itemset-based Data" Special Sessions Paper Information Granulation in Data Science and Scalable Computing，IEEE BIG DATA 2020, December 10-13, 2020, Atlanta, GA, USA.

7. Nannan Lu, Wenjian Luo, Li Ni, Hao Jiang, and Weiping Ding, “Extending CDFR for overlapping community detection,” The First International Conference on Data Intelligence and Security (ICDIS-2018), April 8-10, 2018, South Padre Island, USA. (Best Student Paper Award)

8. Weiping Ding, Senbo Chen, and Xueyun Chen, “A parallel minimum attribute co-reduction accelerator based on quantum-inspired SFLA and MapReduce Framework,” 2015 International Conference on Data Mining and Applications (ICDMA’15),  March 17-20, pp. 280-285, Kowloon, HongKong.  (Best Paper Award)

9. Weiping Ding, Senbo Chen, Xuehua Shen, Qi Gu, and Huiping Liu, “An adaptive minimum attribute reduction algorithm integrating quantum elitists and reverse cloud models,” In: Proceeding of 2013 6rd International Congress on Image and Signal Processing (CISP 2013), Dec 16-18, pp. 555-560, Hangzhou, China. 

10. Weiping Ding, Quan Shi, Senbo Chen, Zhijin Guan, and Jiandong Wang, “A novel quantum cooperative co-evolutionary algorithm for large-scale minimum attribute reduction optimization,” In: Proceedings of IEEE Symposium Series on Computation al Intelligence (SSCI), 2013, April 16-19, pp.280-286. Singapore.

11. Zhijin Guan, Wenjuan Li, Weiping Ding, Yueqin Hang, and Lihui Ni, “An arithmetic logic unit design based on reversible logic gates,” 2011 IEEE Pacific RIM Conference on Communications, Computers, and Signal Processing (PacRim 2011) , pp 925-931, Aug 23-26, 2011, University of Victoria,Victoria, BC, Canada.

12. Weiping Ding, Jiandong Wang, Zhijin Guan, Hao Zhu, and Quan Shi, “Rough knowledge mining algorithm for electronic patient record system based on decision rule lattice,” In: International Conference on Artificial Intelligence and Computational Intelligence, Oct. 23-24, 2010, pp.161-165, Sanya, China

13. Weiping Ding, Zhijin Guan, Quan Shi, and Zhenguo Shi, “Research of electronic patient record mining based on rough concept lattice,” In. The 2009 International IEEE Workshop Conference on Intelligent Systems and Applications, IEEE Computer Science, May 22-24, 2009, pp. 1-4, Wuhan, China. 

14. Weiping Ding, Quan Shi, Zhijin Guan, and Zhenguo Shi, “Research of rough approximation in concept lattice and rules mining,”  In: The Second Annual Conference of Jiangsu Young Scientists, 2008, Sep. 28-29, pp.148-158, Nanjing, China. 

15. Weiping Ding, Xiaolong Xu, and Hen Qi, “Association rules and its application in electronic patient record,” In: The first Annual Conference of Jiangsu Young Scientists, pp.188-193, June 24-25, 2006, Nanjing, China. 

16. Weiping Ding, Weijiang Gu, and Jiancheng Dong, “Application of fuzzy logic reasoning in intelligent assistant diagnosis system of electronic patient record,” In 2007 Advances in Chinese Biomedical Engineering, pp.1274-1278, 2017, Xi’an, China.

Book Chapters

• C++ Programming Basic Tutorial, 2023. 1

• Data Structures,  Science Press, 2021. 12

• Data Structures, Tsing Hua Press, 2014.12 

• Introduction to Computers & Practice, Tsing Hua Press, 2015.9

• C++ Program, Jinban Electron Press, 2008.9

• Deep Learning Techniques for IoT Security and Privacy，Springer Nature, 2021.10

• Intelligent Systems Design and Applications, Springer Nature, 2022.1