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Zhong-kai Feng

Zhong-kai Feng

D-Index & Metrics

Engineering and Technology

D-Index
38
Citations
5046
World Ranking
8136
National Ranking
1438

Overview

Zhong-kai Feng is affiliated with Hohai University in China. Their research primarily focuses on engineering and environmental science, with specific attention to subfields including electrical and electronic engineering, environmental engineering, ocean engineering, water science and technology, and artificial intelligence.

The scientist has published extensively on topics related to hydrological forecasting using artificial intelligence, energy load and power forecasting, water resources management and optimization, hydrology and watershed management studies, electric power system optimization, water systems and optimization, and water-energy-food nexus studies.

Among the recent notable publications are:

  • Monthly runoff time series prediction by variational mode decomposition and support vector machine based on quantum-behaved particle swarm optimization (2020, Journal of Hydrology)
  • Cooperation search algorithm: A novel metaheuristic evolutionary intelligence algorithm for numerical optimization and engineering optimization problems (2020, Applied Soft Computing)
  • Evolutionary artificial intelligence model via cooperation search algorithm and extreme learning machine for multiple scales nonstationary hydrological time series prediction (2021, Journal of Hydrology)
  • Evaluating the performances of several artificial intelligence methods in forecasting daily streamflow time series for sustainable water resources management (2020, Sustainable Cities and Society)
  • Annual Streamflow Time Series Prediction Using Extreme Learning Machine Based on Gravitational Search Algorithm and Variational Mode Decomposition (2020, Journal of Hydrologic Engineering)

Zhong-kai Feng has frequently published in several key venues including:

  • Journal of Hydrology
  • Applied Soft Computing
  • Water Resources Management
  • Journal of Hydrologic Engineering
  • Environmental Research Letters

Frequent collaborators in their research include:

  • Wen-jing Niu
  • Shuai Liu
  • Yinshan Xu
  • Wenchuan Wang
  • Zhiqiang Jiang

In addition to journal publications, Zhong-kai Feng has contributed to book literature, with works published by Frontiers Media, including the 2024 book titled "Key technologies for hybrid energy system planning and operation."

Best Publications

  • A hybrid short-term load forecasting model based on variational mode decomposition and long short-term memory networks considering relevant factors with Bayesian optimization algorithm

    Feifei He;Jianzhong Zhou;Zhong-kai Feng;Guangbiao Liu

  • Monthly runoff time series prediction by variational mode decomposition and support vector machine based on quantum-behaved particle swarm optimization

    Zhong-kai Feng;Wen-jing Niu;Zheng-yang Tang;Zhi-qiang Jiang

  • Probabilistic spatiotemporal wind speed forecasting based on a variational Bayesian deep learning model

    Yongqi Liu;Hui Qin;Zhendong Zhang;Shaoqian Pei

  • Cooperation search algorithm: A novel metaheuristic evolutionary intelligence algorithm for numerical optimization and engineering optimization problems

    Zhong-kai Feng;Wen-jing Niu;Shuai Liu

  • Operation rule derivation of hydropower reservoir by k-means clustering method and extreme learning machine based on particle swarm optimization

    Zhong-kai Feng;Wen-jing Niu;Rui Zhang;Sen Wang

  • A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy

    Zhong-kai Feng;Wen-jing Niu;Wen-chuan Wang;Jian-zhong Zhou

  • Hydropower system operation optimization by discrete differential dynamic programming based on orthogonal experiment design

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng;Sheng-li Liao

  • China’s large-scale hydropower system: operation characteristics, modeling challenge and dimensionality reduction possibilities

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng

  • Multi-stage progressive optimality algorithm and its application in energy storage operation chart optimization of cascade reservoirs

    Zhiqiang Jiang;Changming Ji;Hui Qin;Zhongkai Feng

  • Forecasting reservoir monthly runoff via ensemble empirical mode decomposition and extreme learning machine optimized by an improved gravitational search algorithm

    Wen-jing Niu;Zhong-kai Feng;Ming Zeng;Bao-fei Feng

  • Wind speed forecasting based on Quantile Regression Minimal Gated Memory Network and Kernel Density Estimation

    Zhendong Zhang;Hui Qin;Yongqi Liu;Liqiang Yao

  • A parallel multi-objective particle swarm optimization for cascade hydropower reservoir operation in southwest China

    Wen-jing Niu;Zhong-kai Feng;Chun-tian Cheng;Xin-yu Wu

  • Optimization of hydropower reservoirs operation balancing generation benefit and ecological requirement with parallel multi-objective genetic algorithm

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng

  • Multi-objective quantum-behaved particle swarm optimization for economic environmental hydrothermal energy system scheduling

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng

  • Forecasting Daily Runoff by Extreme Learning Machine Based on Quantum-Behaved Particle Swarm Optimization

    Wen-jing Niu;Zhong-kai Feng;Chun-tian Cheng;Jian-zhong Zhou

  • Annual Streamflow Time Series Prediction Using Extreme Learning Machine Based on Gravitational Search Algorithm and Variational Mode Decomposition

    Wen-jing Niu;Zhong-kai Feng;Yu-bin Chen;Hai-rong Zhang

  • Optimization of hydropower system operation by uniform dynamic programming for dimensionality reduction

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng;Xin-yu Wu

  • Peak shaving operation of hydro-thermal-nuclear plants serving multiple power grids by linear programming

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng;Jian-zhong Zhou

  • Optimizing electrical power production of hydropower system by uniform progressive optimality algorithm based on two-stage search mechanism and uniform design

    Zhong-kai Feng;Wen-jing Niu;Chun-tian Cheng

  • Parallel Multi-Objective Genetic Algorithm for Short-Term Economic Environmental Hydrothermal Scheduling

    Zhong-Kai Feng;Wen-Jing Niu;Jian-Zhong Zhou;Chun-Tian Cheng

  • Evolutionary artificial intelligence model via cooperation search algorithm and extreme learning machine for multiple scales nonstationary hydrological time series prediction

    Zhong-kai Feng;Wen-jing Niu;Zheng-yang Tang;Yang Xu

Frequent Co-Authors

Chuntian Cheng
Chuntian Cheng Dalian University of Technology
Jianzhong Zhou
Jianzhong Zhou Huazhong University of Science and Technology
Jay R. Lund
Jay R. Lund University of California, Davis

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