Prince, Hati, A.S., 2021. A comprehensive review of energy-efficiency of ventilation system using Artificial Intelligence. Renewable and Sustainable Energy Reviews, 146, p.111153, DOI: https://doi.org/10.1016/j.rser.2021.111153
Prince, Hati, A.S., Chakrabarti, P. et al. 2021. Development of energy-efficient drive for ventilation system using recurrent neural network. Neural Comput & Applic 33, p.8659–8668, DOI: https://doi.org/10.1007/s00521-020-05615-x
Prince, Hati, A.S., 2021. Temperature and humidity dependent mras based speed estimation technique for induction motor used in mine ventilation drive. Journal of Mining Sciences. 5, pp 150-159, DOI: https://doi.org/10.1134/S1062739121050148
Prince, Hati, A.S., 2022. Convolutional Neural Network-Long Short Term Memory Optimization for Accurate Prediction of Airflow in a Ventilation System. Expert Systems With Applications, https://doi.org/10.1016/j.eswa.2022.116618
Prince, Hati, AS, and Kumar, P., 2023. An adaptive neural fuzzy interface structure optimisation for prediction of energy consumption and airflow of a ventilation system. Applied Energy, 337, p.120879, DOI: https://doi.org/10.1016/j.apenergy.2023.120879 (Impact Factor: 11.446, SCIE)
Kumar, P., Prince, Hati, A. S., & Kim, H. S. (2022). Deep Transfer Learning Framework for Bearing Fault Detection in Motors. Mathematics, 10(24), 4683. DOI: https://doi.org/10.3390/math10244683 (IF: 2.592, SCIE)
Tiwari, S. K., Kumaraswamidhas, L. A., Prince, Kamal, M., & Rehman, M. U. (2023). A hybrid deep learning model for prediction and parametric sensitivity analysis of noise annoyance. Environmental Science and Pollution Research, 1-19. DOI: https://doi.org/10.1007/s11356-023-25509-4 (IF: 5.910, SCIE)
Kumar, P., Prince, & Hati, A. S. (2023). A transfer learning-based deep convolutional neural network approach for induction machine multiple faults detection. International Journal of Adaptive Control and Signal Processing, 37, p. 1-14, DOI: https://doi.org/10.1002/acs.3643 (IF:3.369, SCIE)
Vadavadagi, S. S., Chawla, S., & Prince. (2024). Prediction and validation of geogrid tensile force distribution in back-to-back MSE walls under rail axle load: finite-element and intelligent techniques. Environmental Earth Sciences, 83(5), 149 (IF:2.8, SCIE).
Kumar, P., Raouf, I., Song, J., Prince & Kim, H. S. (2024). Multi-size wide kernel convolutional neural network for bearing fault diagnosis. Advances in Engineering Software, 198, 103799, DOI: https://doi.org/10.1016/j.advengsoft.2024.103799 (IF:4.0, SCIE)
Kumar, P., Prince, Sinha, A. K., & Kim, H. S. (2024). Electric Vehicle Motor Fault Detection with Improved Recurrent 1D Convolutional Neural Network. Mathematics (2227-7390), 12(19), DOI: https://doi.org/10.3390/math12193012 (IF:2.3, SCIE).
Gupta, Varun, Vivek Kumar, Prince, Saurabh Singh, Young-Seok Lee, and In-Ho Ra. "Deep Learning Model for Analyzing EEG Signal Analysis." IEEE Access (2025). DOI: 10.1109/ACCESS.2025.3563760 (IF: 5.7, SCIE: 3.6)
Prince, and Byungun Yoon. "Super Twisted Sliding Mode Observer for Enhancing Ventilation Drive Performance." Applied Sciences 15, no. 9 (2025): 4927. DOI: https://doi.org/10.3390/app15094927 (IF: 2.5, SCIE)
Prince, Byungun Yoon, and Prashant Kumar. "Fault Detection and Diagnosis in Air-Handling Unit (AHU) Using Improved Hybrid 1D Convolutional Neural Network." Systems 13, no. 5 (2025): 330. DOI: https://doi.org/10.3390/systems13050330 (IF: 3.1, SCIE)
Prince, Byungun Yoon, Ananda Shankar Hati, Prashant Kumar, and Prasun Chakrabarti. "Prediction of Energy Consumption and Airflow of a Ventilation System: A SAGA-Optimised Back-Propagation Neural Network-based Approach." Expert Systems with Applications (2025): 129293.https://doi.org/10.1016/j.eswa.2025.129293 (IF: 7.5, SCIE)
Prince, Byungun Yoon, and Prashant Kumar. "Enhanced Fault Diagnosis of Drive-Fed Induction Motors Using a Multi-Scale Wide-Kernel CNN." Mathematics 13, no. 18 (2025): 2963. https://doi.org/10.3390/math13182963 (IF:2.3, SCIE).
Prince, Biswas, M, Hati, A.S., 2018. Development of energy-efficient and intelligent mine ventilation system. Proceedings of Technological Advancement and Emerging Mining Methods, pp 286-296.
A. K. Sinha, Prince, P. Kumar, and A. S. Hati, ANN-Based Fault Detection Scheme for Bearing Condition Monitoring in SRIMs using FFT, DWT and Band-pass Filters. 2020 International Conference on Power, Instrumentation, Control and Computing (PICC), 2020, pp. 1-6, DOI: 10.1109/PICC51425.2020.9362486.
Prince, Hati, A.S., Sensor-less Speed Control of Ventilation System Using Extended Kalman Filter For High Performance. 2021 IEEE 8th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON), 2021, pp. 1-6, DOI: 10.1109/UPCON52273.2021.9667633.
Kumar, P., Prince, Hati, A. S., & Kim, H. S. (2023). Bearing Fault Diagnosis in Induction Motor using hybrid CNN model. Lecture Notes in Mechanical Engineering, Springer.
Sinha, Ashish Kumar, Prashant Kumar, and Prince Kumar. "Electric Vehicle: Types, Charging Topologies, Energy Storage Management System and Applicability Micro-Grids–A Review." (2024).