| Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm C Li, J Zhou Energy Conversion and Management 52 (1), 374-381, 2011 | 332 | 2011 |
| Short-term wind speed interval prediction based on ensemble GRU model C Li, G Tang, X Xue, A Saeed, X Hu IEEE transactions on sustainable energy 11 (3), 1370-1380, 2019 | 266 | 2019 |
| A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting C Zhang, J Zhou, C Li, W Fu, T Peng Energy Conversion and Management 143, 360-376, 2017 | 266 | 2017 |
| Load frequency control of a novel renewable energy integrated micro-grid containing pumped hydropower energy storage Y Xu, C Li, Z Wang, N Zhang, B Peng Ieee Access 6, 29067-29077, 2018 | 183 | 2018 |
| Design of a fractional-order PID controller for a pumped storage unit using a gravitational search algorithm based on the Cauchy and Gaussian mutation C Li, N Zhang, X Lai, J Zhou, Y Xu Information Sciences 396, 162-181, 2017 | 175 | 2017 |
| Deep learning method based on gated recurrent unit and variational mode decomposition for short-term wind power interval prediction R Wang, C Li, W Fu, G Tang IEEE transactions on neural networks and learning systems 31 (10), 3814-3827, 2019 | 173 | 2019 |
| Multi-step short-term wind speed forecasting approach based on multi-scale dominant ingredient chaotic analysis, improved hybrid GWO-SCA optimization and ELM W Fu, K Wang, C Li, J Tan Energy Conversion and Management 187, 356-377, 2019 | 168 | 2019 |
| A hybrid model based on synchronous optimisation for multi-step short-term wind speed forecasting C Li, Z Xiao, X Xia, W Zou, C Zhang Applied Energy 215, 131-144, 2018 | 155 | 2018 |
| An adaptively fast fuzzy fractional order PID control for pumped storage hydro unit using improved gravitational search algorithm Y Xu, J Zhou, X Xue, W Fu, W Zhu, C Li Energy Conversion and Management 111, 67-78, 2016 | 153 | 2016 |
| An adaptively fast ensemble empirical mode decomposition method and its applications to rolling element bearing fault diagnosis X Xue, J Zhou, Y Xu, W Zhu, C Li Mechanical Systems and Signal Processing 62, 444-459, 2015 | 146 | 2015 |
| T–S fuzzy model identification with a gravitational search-based hyperplane clustering algorithm C Li, J Zhou, B Fu, P Kou, J Xiao IEEE Transactions on Fuzzy Systems 20 (2), 305-317, 2011 | 146 | 2011 |
| Temporal convolutional networks interval prediction model for wind speed forecasting Z Gan, C Li, J Zhou, G Tang Electric Power Systems Research 191, 106865, 2021 | 141 | 2021 |
| A novel chaotic particle swarm optimization based fuzzy clustering algorithm C Li, J Zhou, P Kou, J Xiao Neurocomputing 83, 98-109, 2012 | 139 | 2012 |
| T–S fuzzy model identification based on a novel fuzzy c-regression model clustering algorithm C Li, J Zhou, X Xiang, Q Li, X An Engineering Applications of Artificial Intelligence 22 (4-5), 646-653, 2009 | 139 | 2009 |
| Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm W Wang, C Li, X Liao, H Qin Applied energy 187, 612-626, 2017 | 132 | 2017 |
| Compound feature selection and parameter optimization of ELM for fault diagnosis of rolling element bearings M Luo, C Li, X Zhang, R Li, X An Isa Transactions 65, 556-566, 2016 | 124 | 2016 |
| Parameters identification of chaotic system by chaotic gravitational search algorithm C Li, J Zhou, J Xiao, H Xiao Chaos, Solitons & Fractals 45 (4), 539-547, 2012 | 118 | 2012 |
| EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning X Peng, H Wang, J Lang, W Li, Q Xu, Z Zhang, T Cai, S Duan, F Liu, C Li Energy 220, 119692, 2021 | 106 | 2021 |
| The short-term interval prediction of wind power using the deep learning model with gradient descend optimization C Li, G Tang, X Xue, X Chen, R Wang, C Zhang Renewable Energy 155, 197-211, 2020 | 98 | 2020 |
| Adaptive condition predictive-fuzzy PID optimal control of start-up process for pumped storage unit at low head area Y Xu, Y Zheng, Y Du, W Yang, X Peng, C Li Energy Conversion and Management 177, 592-604, 2018 | 97 | 2018 |
Xiaoyuan zhangDepartment of Electrical Engineering Henan University of Technology, ChinaПотвърден имейл адрес: haut.edu.cn