| Q-learning-based vulnerability analysis of smart grid against sequential topology attacks J Yan, H He, X Zhong, Y Tang IEEE Transactions on Information Forensics and Security 12 (1), 200-210, 2016 | 289 | 2016 |
| Stochastic optimization of economic dispatch for microgrid based on approximate dynamic programming H Shuai, J Fang, X Ai, Y Tang, J Wen, H He IEEE Transactions on Smart Grid 10 (3), 2440-2452, 2018 | 283 | 2018 |
| Stacked multilevel-denoising autoencoders: A new representation learning approach for wind turbine gearbox fault diagnosis G Jiang, H He, P Xie, Y Tang IEEE Transactions on Instrumentation and Measurement 66 (9), 2391-2402, 2017 | 280 | 2017 |
| Cascading Failure Analysis With DC Power Flow Model and Transient Stability Analysis J Yan, Y Tang, H He, Y Sun Power Systems, IEEE Transactions on, 1-13, 2014 | 252 | 2014 |
| Improved sliding mode design for load frequency control of power system integrated an adaptive learning strategy C Mu, Y Tang, H He IEEE Transactions on Industrial Electronics 64 (8), 6742-6751, 2017 | 241 | 2017 |
| Power system stability control for a wind farm based on adaptive dynamic programming Y Tang, H He, J Wen, J Liu IEEE Transactions on Smart Grid 6 (1), 166-177, 2014 | 197 | 2014 |
| Energy-Storage-Based Low-Frequency Oscillation Damping Control Using Particle Swarm Optimization and Heuristic Dynamic Programming X Sui, Y Tang, H He, J Wen Power Systems, IEEE Transactions on, 1-10, 2014 | 184 | 2014 |
| Load frequency control in isolated micro-grids with electrical vehicles based on multivariable generalized predictive theory J Yang, Z Zeng, Y Tang, J Yan, H He, Y Wu Energies 8 (3), 2145-2164, 2015 | 183 | 2015 |
| An event-triggered approach for load frequency control with supplementary ADP L Dong, Y Tang, H He, C Sun IEEE Transactions on Power Systems 32 (1), 581-589, 2017 | 175 | 2017 |
| Optimized Control of DFIG-Based Wind Generation Using Sensitivity Analysis and Particle Swarm Optimization Y Tang, P Ju, H He, C Qin, F Wu Smart Grid, IEEE Transactions on 4 (1), 509 - 520, 2013 | 174 | 2013 |
| Multi-class imbalanced graph convolutional network learning M Shi, Y Tang, X Zhu, D Wilson, J Liu Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 164 | 2020 |
| Resilience analysis of power grids under the sequential attack Y Zhu, J Yan, Y Tang, YL Sun, H He IEEE Transactions on Information Forensics and Security 9 (12), 2340-2354, 2014 | 136 | 2014 |
| Reactive power control of grid-connected wind farm based on adaptive dynamic programming Y Tang, H He, Z Ni, J Wen, X Sui Neurocomputing 125, 125-133, 2014 | 121 | 2014 |
| A deep imbalanced learning framework for transient stability assessment of power system B Tan, J Yang, Y Tang, S Jiang, P Xie, W Yuan Ieee Access 7, 81759-81769, 2019 | 99 | 2019 |
| Functional and contextual attention-based LSTM for service recommendation in mashup creation M Shi, J Liu IEEE Transactions on Parallel and Distributed Systems 30 (5), 1077-1090, 2018 | 83 | 2018 |
| Deep learning-aided cyber-attack detection in power transmission systems D Wilson, Y Tang, J Yan, Z Lu 2018 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2018 | 76 | 2018 |
| Joint substation-transmission line vulnerability assessment against the smart grid Y Zhu, J Yan, Y Tang, YL Sun, H He IEEE transactions on Information Forensics and Security 10 (5), 1010-1024, 2015 | 76 | 2015 |
| Genetic-gnn: Evolutionary architecture search for graph neural networks M Shi, Y Tang, X Zhu, Y Huang, D Wilson, Y Zhuang, J Liu Knowledge-based systems 247, 108752, 2022 | 75 | 2022 |
| Intelligent load frequency controller using GrADP for island smart grid with electric vehicles and renewable resources Y Tang, J Yang, J Yan, H He Neurocomputing 170, 406-416, 2015 | 74 | 2015 |
| A bi-layer optimization based temporal and spatial scheduling for large-scale electric vehicles L He, J Yang, J Yan, Y Tang, H He Applied energy 168, 179-192, 2016 | 70 | 2016 |
Haibo HeUniversity of Rhode Islanduri.edu의 이메일 확인됨