A) Feature Extraction (1 paper)
W. Lin, J. Huang, C. Suen, L. Yang, "A Feature Extraction Model based on Discriminative Graph Signals", Expert Systems with Applications, Volume 139, January 2021.
B) Forecasting (13 papers)
Time Series Forecasting (1 paper)
D. Cheng, F. Yang, S. Xiang, J. Liu, “Financial Time Series Forecasting with Multi-Modality Graph Neural Network”, Pattern Recognition, 2022.
Traffic Forecasting (12 papers)
Q. Mei, Z. Li, Q. Hu, X. Zhi, P. Wang, Y. Yang, X. Liu, "Spatio-temporal Graph Neural Network Fused with Maritime Knowledge for Predicting Traffic Flows in Ports", Regional Studies in Marine Science, March 2025.
G. Liang, P. Tiwari, S. Nowaczyk, S. Byttner, F. Alonso-Fernandez, "Dynamic Causal Explanation based Diffusion-Variational Graph Neural Network for Spatiotemporal Forecasting", IEEE Transactions on Neural Networks and Learning Systems , 2024.
T. Mallick, J. Macfarlane, P. Balaprakash, "Uncertainty Quantification for Traffic Forecasting using Deep-Ensemble-based Spatiotemporal Graph Neural Networks", IEEE Transactions on Intelligent Transportation Systems, 2024.
C. Zheng, X. Fan, S. Pan, H. Jin, Z. Peng, Z. Wu, "Spatio-Temporal Joint Graph Convolutional Networks for Traffic Forecasting", IEEE Transactions on Knowledge and Data Engineering, Volume 36, No. 1, pages 372-385, 2024.
A. Einizade, F. Malliaros, J. Giraldo, “Continuous Product Graph Neural Networks”, Preprint, May 2024.
A. Einizade, F. Malliaros, J. Giraldo, “Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks”, Preprint, May 2024.
Z. Li, J. Yu, G. Zhang, L. Xu, “Dynamic spatiotemporal graph network with adaptive propagation mechanism for multivariate time series forecasting", Expert Systems with Applications, Volume 216, page 119374, 2023.
W. Zhang, K. Zhu, S. Zhang, Q. Chen, J. Xu, “Dynamic graph convolutional networks based on spatiotemporal data embedding for traffic flow forecasting ", Knowledge-Based Systems, page 109028, 2022.
F. Zhou, Q. Yang, T. Zhong, D. Chen, N. Zhang, “Variational graph neural networks for road traffic prediction in intelligent transportation systems", IEEE Transactions on Industrial Informatics, Volume 17, No. 4, page 2802–2812, 2020.
K. Tian, J. Guo, K. Yen, C. Xu, "ST-MGAT: Spatial-Temporal Multi-Head Graph Attention Networks for Traffic Forecasting", IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2020, 2020.
J. Wang, Q. Chen H. Gong, "STMAG: A spatial–temporal mixed attention graph-based convolution model for multi-data flow safety prediction", Information Sciences, 2020
Y. Wang, Y. Ma, Y. Wang, W. Jin, X. Wang, J. Tang, "Traffic flow prediction via spatial temporal graph neural network", Web Conference, pages 1082–1092, 2020.
L. Bai L. Yao, C. Li, X. Wang, C. Wang, "Adaptive graph convolutional recurrent network for traffic forecasting", Conference on Neural Information Processing Systems, NeurIPS 2020, 2020.
Transportation Networks (1 paper)
T. Liu, A. Jiang, X. Miao, Y. Tang, Y. Zhu, H. Kwan, “Graph-based dynamic modeling and traffic prediction of urban road network", IEEE Sensors Journal, Volume 21, No. 24, pages 118-130, 2021.
C) Ecology (17 papers)
Air Quality (2 papers)
J. Jin, J. Zhang, J. Tang, S. Liang, Z. Qu, "Spatio-Temporal Data Mining with Information Integrity Protection: Graph Signal Based Air Quality Prediction”, IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2024, Seoul, South Korea, pages 5190-5194, 2024.
J. Xu, L. Chen, M. Lv, C. Zhan, S. Chen, “HighAir: A Hierarchical Graph Neural Network-Based Air Quality Forecasting Method”, Preprint, 2021.
Renewable Energy (3 papers)
X. Zhang, J. Shi, J. Li, X. Huang, F. Xiao, Q. Wang, A. Usmani, G. Chen, “Hydrogen Jet and Diffusion Modeling by Physics-Informed Graph Neural Network”, Renewable and Sustainable Energy Reviews, Volume 207, January 2025.
Q. Wu, H. Zheng, X. Guo, G. Liu, “Promoting Wind Energy for Sustainable Development by Precise Wind Speed Prediction Based on Graph Neural Networks”, Renewable Energy, 2022.
J. Park, J. Park, "Physics-induced Graph Neural Network: An Application to Wind-Farm Power Estimation”, Energy, 2019.
Wind (11 papers)
G. Hou, Q. Li, C. Huang, “Spatiotemporal Forecasting using Multi-Graph Neural Network Assisted Dual Domain Transformer for Wind Power”, Energy Conversion and Management, Volume 325, February 2025.
H. Qiu, K. Shi, R. Wang, L. Zhang, X. Liu, X. Cheng, "A Novel Temporal–Spatial Graph Neural Network for Wind Power Forecasting Considering Blockage Effects”, Renewable Energy, 2024.
B. Zhao, X. He, S. Ran, Y. Zhang, C. Cheng, “Spatial Correlation Learning based on Graph Neural Network for Medium-Term Wind Power Forecasting”, Energy, 2024.
X. Liu, Y. Zhang, Z. Zhen, F. Xu, F. Wang , Z. Mi, "Spatio-Temporal Graph Neural Network and Pattern Prediction Based Ultra-Short-Term Power Forecasting of Wind Farm Cluster", IEEE Transactions on Industry Applications, Volume 60, No. 1, pages 1794-1803, January 2024.
J Liu, X Wang, F Xie, S Wu, D Li, “Condition Monitoring of Wind Turbines with The Implementation Of Spatio-Temporal Graph Neural Network”, Engineering Applications of Artificial Intelligence, 2023.
Z. Gao, Z. Li, L. Xu, J. Yu, “Dynamic Adaptive Spatio-Temporal Graph Neural Network for Multi-Node Offshore Wind Speed Forecasting”, Applied Soft Computing, 2023.
X. Shao, Z. Liu, S. Zhang, Z. Zhao, C. Hu, "PIGNN-CFD: A Physics-Informed Graph Neural Network for Rapid Predicting Urban Wind Field Defined on Unstructured Mesh", Building and Environment, 2023.
Z. Liu, S. Zhang, X. Shao, Z. Wu, "Accurate and Efficient Urban Wind Prediction at City-Scale with Memory-Scalable Graph Neural Network", Sustainable Cities and Society, 2023.
Z. Liu, T. Ware, “Capturing Spatial Influence in Wind Prediction with a Graph Convolutional Neural Network”, Frontiers in Environmental Science, 2022.
M. Yu, Z. Zhang, X. Li, J. Yu, J. Gao, Z. Liu, B. Yo, X. Zheng, R. Yu, “Superposition Graph Neural Network for Offshore Wind Power Prediction”, Future Generation Computer Systems, 2020.
Temperature (1 paper)
P. Xu, S. Xu, K. Shi, M. Ou, H. Zhu, G. Xu, D. Gao, G. Li ,“Prediction of Water Temperature Based on Graph Neural Network in A Small-Scale Observation via Coastal Acoustic Tomography”, MDPI Remote Sensing, 2024.