World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
6976
World Ranking
6260
National Ranking
836

Overview

Chaoshun Li is affiliated with the Huazhong University of Science and Technology in China, specializing in engineering disciplines. Their research primarily focuses on electrical and electronic engineering, control and systems engineering, mechanics of materials, civil and structural engineering, and artificial intelligence.

Their numerous publications contribute significantly to fields such as energy load and power forecasting, machine fault diagnosis techniques, power system optimization and stability, cavitation phenomena in pumps, electric power system optimization, water systems and optimization, and microgrid control and optimization.

Frequent publication venues for their work include:

  • Energy
  • Renewable Energy
  • SSRN Electronic Journal
  • IEEE Access
  • Journal of Energy Storage

Notable recent papers authored by Chaoshun Li include:

  • The short-term interval prediction of wind power using the deep learning model with gradient descend optimization, 2020, Renewable Energy

Other significant papers from related research include:

  • Temporal convolutional networks interval prediction model for wind speed forecasting, 2020, Electric Power Systems Research
  • EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning, 2020, Energy
  • A Novel Wind Speed Interval Prediction Based on Error Prediction Method, 2020, IEEE Transactions on Industrial Informatics
  • A novel fault diagnosis procedure based on improved symplectic geometry mode decomposition and optimized SVM, 2020, Measurement

Chaoshun Li collaborates frequently with several coauthors, including:

  • Xueding Lu (18 joint publications)
  • Xiaoqiang Tan (16 joint publications)
  • Zhiwei Zhu (14 joint publications)
  • Dong Liu (13 joint publications)
  • Jie Huang (11 joint publications)

Their research integrates deep learning models and optimization techniques applied to wind power and energy forecasting, emphasizing interval prediction methodologies. The work typically intersects machine learning approaches with power system applications, addressing both theoretical and practical challenges in renewable energy forecasting and system stability.

Best Publications

  • Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm

    Chaoshun Li;Jianzhong Zhou

  • Short-Term Wind Speed Interval Prediction Based on Ensemble GRU Model

    Chaoshun Li;Geng Tang;Xiaoming Xue;Adnan Saeed

  • A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting

    Chu Zhang;Jianzhong Zhou;Chaoshun Li;Wenlong Fu

  • Design of a fractional-order PID controller for a pumped storage unit using a gravitational search algorithm based on the Cauchy and Gaussian mutation

    Chaoshun Li;Nan Zhang;Xinjie Lai;Jianzhong Zhou

  • Deep Learning Method Based on Gated Recurrent Unit and Variational Mode Decomposition for Short-Term Wind Power Interval Prediction

    Ruoheng Wang;Chaoshun Li;Wenlong Fu;Geng Tang

  • Load Frequency Control of a Novel Renewable Energy Integrated Micro-Grid Containing Pumped Hydropower Energy Storage

    Yanhe Xu;Chaoshun Li;Zanbin Wang;Nan Zhang

  • Multi-step short-term wind speed forecasting approach based on multi-scale dominant ingredient chaotic analysis, improved hybrid GWO-SCA optimization and ELM

    Wenlong Fu;Kai Wang;Chaoshun Li;Jiawen Tan

  • Temporal convolutional networks interval prediction model for wind speed forecasting

    Zhenhao Gan;Chaoshun Li;Jianzhong Zhou;Geng Tang

  • An adaptively fast fuzzy fractional order PID control for pumped storage hydro unit using improved gravitational search algorithm

    Yanhe Xu;Jianzhong Zhou;Xiaoming Xue;Wenlong Fu

  • T–S Fuzzy Model Identification With a Gravitational Search-Based Hyperplane Clustering Algorithm

    Chaoshun Li;Jianzhong Zhou;Bo Fu;Pangao Kou

  • A hybrid model based on synchronous optimisation for multi-step short-term wind speed forecasting

    Chaoshun Li;Zhengguang Xiao;Xin Xia;Wen Zou

  • An adaptively fast ensemble empirical mode decomposition method and its applications to rolling element bearing fault diagnosis

    Xiaoming Xue;Jianzhong Zhou;Yanhe Xu;Wenlong Zhu

  • T-S fuzzy model identification based on a novel fuzzy c-regression model clustering algorithm

    Chaoshun Li;Jianzhong Zhou;Xiuqiao Xiang;Qingqing Li

  • Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm

    Wenxiao Wang;Chaoshun Li;Xiang Liao;Hui Qin

  • Compound feature selection and parameter optimization of ELM for fault diagnosis of rolling element bearings.

    Meng Luo;Chaoshun Li;Xiaoyuan Zhang;Ruhai Li

  • EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning

    Xiaosheng Peng;Hongyu Wang;Jianxun Lang;Wenze Li

  • A novel chaotic particle swarm optimization based fuzzy clustering algorithm

    Chaoshun Li;Jianzhong Zhou;Pangao Kou;Jian Xiao

  • Parameters identification of chaotic system by chaotic gravitational search algorithm

    Chaoshun Li;Jianzhong Zhou;Jian Xiao;Han Xiao

  • Adaptive condition predictive-fuzzy PID optimal control of start-up process for pumped storage unit at low head area

    Yanhe Xu;Yang Zheng;Yi Du;Wen Yang

  • The short-term interval prediction of wind power using the deep learning model with gradient descend optimization

    Chaoshun Li;Geng Tang;Xiaoming Xue;Xinbiao Chen

  • Multi-objective complementary scheduling of hydro-thermal-RE power system via a multi-objective hybrid grey wolf optimizer

    Chaoshun Li;Wenxiao Wang;Deshu Chen

Frequent Co-Authors

Jianzhong Zhou
Jianzhong Zhou Huazhong University of Science and Technology
Diyi Chen
Diyi Chen Northwest A&F University
Shanxu Duan
Shanxu Duan Huazhong University of Science and Technology
Om P. Malik
Om P. Malik University of Calgary
Pak Kin Wong
Pak Kin Wong University of Macau

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