| Online sequential extreme learning machine with kernels for nonstationary time series prediction X Wang, M Han Neurocomputing 145, 90-97, 2014 | 226 | 2014 |
| A decision making strategy for generating unit tripping under emergency circumstances based on deep reinforcement learning W Liu, D Zhang, X Wang, J Hou, L Liu Proceedings of the CSEE 38 (1), 109-119, 2018 | 80 | 2018 |
| Improved extreme learning machine for multivariate time series online sequential prediction X Wang, M Han Engineering Applications of Artificial Intelligence 40, 28-36, 2015 | 74 | 2015 |
| Research and application of artificial intelligence in operation and maintenance for power equipment T Pu, J Qiao, X Han, GB Zhang, XY Wang High Voltage Engineering 46 (2), 369-383, 2020 | 63 | 2020 |
| Spatio-temporal convolutional network based power forecasting of multiple wind farms X Dong, Y Sun, Y Li, X Wang, T Pu Journal of Modern Power Systems and Clean Energy 10 (2), 388-398, 2021 | 44 | 2021 |
| Renewable scenario generation using controllable generative adversarial networks with transparent latent space J Qiao, T Pu, X Wang CSEE Journal of Power and Energy Systems 7 (1), 66-77, 2020 | 38 | 2020 |
| Preventive control for power system transient security based on XGBoost and DCOPF with consideration of model interpretability S Zhang, D Zhang, J Qiao, X Wang, Z Zhang CSEE Journal of Power and Energy Systems 7 (2), 279-294, 2020 | 36 | 2020 |
| Power system transient stability analysis based on random matrix theory W Liu, D Zhang, X Wang, D Liu, Q Wu Proc. CSEE 36 (18), 4854-4863, 2016 | 35 | 2016 |
| 基于极端学习机的多变量混沌时间序列预测 王新迎， 韩敏 物理学报 61 (8), 97-105, 2012 | 33* | 2012 |
| 多元混沌时间序列的多核极端学习机建模预测 王新迎， 韩敏 物理学报 64 (7), 70504-070504, 2015 | 31* | 2015 |
| Multivariate time series prediction based on multiple kernel extreme learning machine X Wang, M Han 2014 International joint conference on neural networks (IJCNN), 198-201, 2014 | 30 | 2014 |
| 人工智能技术在电力设备运维检修中的研究及应用 蒲天骄， 乔骥， 韩笑， 张国宾， 王新迎 高电压技术 46 (2), 369-383, 2020 | 27 | 2020 |
| Analysis of users’ electricity consumption behavior based on ensemble clustering Q Zhao, H Li, X Wang, T Pu, J Wang Global Energy Interconnection 2 (6), 479-488, 2019 | 26 | 2019 |
| Key technologies and perspectives of power internet of things facing with digital twins of the energy internet Z Peng, P Tianjiao, W Xinying Proceedings of the CSEE 42 (2), 447-457, 2022 | 23 | 2022 |
| Key technologies and perspectives of power internet of things facing with digital twins of the energy internet P Zhao, TJ Pu, XY Wang, X Han Proceedings of the CSEE 42 (2), 447-457, 2022 | 23 | 2022 |
| Load shedding control strategy in power grid emergency state based on deep reinforcement learning J Li, S Chen, X Wang, T Pu CSEE Journal of Power and Energy Systems 8 (4), 1175-1182, 2021 | 22 | 2021 |
| 面向能源互联网数字孪生的电力物联网关键技术及展望 赵鹏， 蒲天骄， 王新迎， 韩笑 中国电机工程学报 42 (2), 447-457, 2022 | 21 | 2022 |
| Power flow adjustment for smart microgrid based on edge computing and multi-agent deep reinforcement learning T Pu, X Wang, Y Cao, Z Liu, C Qiu, J Qiao, S Zhang Journal of Cloud Computing 10, 1-13, 2021 | 21 | 2021 |
| Digital twin modeling for photovoltaic panels based on hybrid neural network G Zhang, X Wang 2021 IEEE 1st International Conference on Digital Twins and Parallel …, 2021 | 21 | 2021 |
| 能源互联网数字孪生系统框架设计及应用展望 蒲天骄， 陈盛， 赵琦， 王新迎， 张东霞 中国电机工程学报 41 (6), 2012-2028, 2021 | 20 | 2021 |
Min HanDalian University of Technology在 dlut.edu.cn 的电子邮件经过验证
