World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
5018
World Ranking
9894
National Ranking
1246

Overview

Zhile Yang is affiliated with the University of Chinese Academy of Sciences in China. Their research spans several fields, primarily focusing on engineering and computer science. Yang's work is notably situated within the subfields of Electrical and Electronic Engineering, Artificial Intelligence, Industrial and Manufacturing Engineering, Control and Systems Engineering, and Computational Theory and Mathematics.

The scientist's main topics of research include metaheuristic optimization algorithms, smart grid energy management, advanced battery technologies, multi-objective optimization algorithms, energy load and power forecasting, electric vehicles and infrastructure, and electric power system optimization.

Zhile Yang has published numerous papers across a variety of scientific venues. The most frequent publication venues include Energy, SSRN Electronic Journal, Knowledge-Based Systems, Machines, and Energies. Some notable recent papers are:

  • "Natural language processing for smart construction: Current status and future directions" (2021, Automation in Construction)
  • "Diabetic Retinopathy Diagnosis Using Multichannel Generative Adversarial Network With Semisupervision" (2020, IEEE Transactions on Automation Science and Engineering)
  • "A review of the potential of district heating system in Northern China" (2021, Applied Thermal Engineering)
  • "A novel competitive swarm optimized RBF neural network model for short-term solar power generation forecasting" (2020, Neurocomputing)
  • "A comprehensive review on deep learning approaches in wind forecasting applications" (2022, CAAI Transactions on Intelligence Technology)

Frequent collaborators in Yang's work include Yuanjun Guo, Chengke Wu, Qinge Xiao, Dongsheng Yang, and Kang Li.

In addition to journal articles, Zhile Yang has contributed to book publications. Two titles published by Springer Science+Business Media are "Recent Advances in Sustainable Energy and Intelligent Systems" (2021) and "Recent Featured Applications of Artificial Intelligence Methods. LSMS 2020 and ICSEE 2020 Workshops" (2020).

Best Publications

  • Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review

    Zhile Yang;Kang Li;Aoife Foley

  • Lithium-ion battery charging management considering economic costs of electrical energy loss and battery degradation

    Kailong Liu;Xiaosong Hu;Zhile Yang;Yi Xie

  • Electric vehicle charging load forecasting: A comparative study of deep learning approaches

    Juncheng Zhu;Zhile Yang;Monjur Mourshed;Yuanjun Guo

  • Multi-population techniques in nature inspired optimization algorithms: A comprehensive survey

    Haiping Ma;Shigen Shen;Mei Yu;Zhile Yang

  • Dynamic opposite learning enhanced teaching–learning-based optimization

    Yunlang Xu;Zhile Yang;Xiaoping Li;Huazhou Kang

  • Biogeography-Based Optimization: A 10-Year Review

    Haiping Ma;Dan Simon;Patrick Siarry;Zhile Yang

  • Short-Term Load Forecasting for Electric Vehicle Charging Stations Based on Deep Learning Approaches

    Juncheng Zhu;Zhile Yang;Yuanjun Guo;Jiankang Zhang

  • Diabetic Retinopathy Diagnosis Using Multichannel Generative Adversarial Network With Semisupervision

    Shuqiang Wang;Xiangyu Wang;Yong Hu;Yanyan Shen

  • A self-learning TLBO based dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

    Zhile Yang;Kang Li;Qun Niu;Yusheng Xue

  • Multi-objective biogeography-based optimization for dynamic economic emission load dispatch considering plug-in electric vehicles charging

    Haiping Ma;Haiping Ma;Zhile Yang;Pengcheng You;Minrui Fei

  • A novel competitive swarm optimized RBF neural network model for short-term solar power generation forecasting

    Zhile Yang;Zhile Yang;Monjur M. Mourshed;Kailong Liu;Xinzhi Xu

  • Mass load prediction for lithium-ion battery electrode clean production: A machine learning approach

    Kailong Liu;Zhongbao Wei;Zhile Yang;Kang Li

  • An advanced Lithium-ion battery optimal charging strategy based on a coupled thermoelectric model

    Kailong Liu;Kang Li;Zhile Yang;Cheng Zhang

  • A compact and optimized neural network approach for battery state-of-charge estimation of energy storage system

    Yuanjun Guo;Zhile Yang;Kailong Liu;Yanhui Zhang

  • Biogeography-based learning particle swarm optimization for combined heat and power economic dispatch problem

    Xu Chen;Kangji Li;Bin Xu;Zhile Yang

  • Automotive Battery Equalizers Based on Joint Switched-Capacitor and Buck-Boost Converters

    Kailong Liu;Zhile Yang;Xiaopeng Tang;Wenping Cao

  • Dynamic opposite learning enhanced dragonfly algorithm for solving large-scale flexible job shop scheduling problem

    Unknown

  • Time series wind power forecasting based on variant Gaussian Process and TLBO

    Juan Yan;Kang Li;Erwei Bai;Zhile Yang

  • Demand side management of plug-in electric vehicles and coordinated unit commitment: A novel parallel competitive swarm optimization method

    Ying Wang;Zhile Yang;Zhile Yang;Monjur Mourshed;Yuanjun Guo

  • Iterative Learning Identification and Compensation of Space-Periodic Disturbance in PMLSM Systems With Time Delay

    Fazhi Song;Yang Liu;Jian-Xin Xu;Xiaofeng Yang

  • A novel hybrid teaching learning based multi-objective particle swarm optimization

    Tingli Cheng;Minyou Chen;Peter J. Fleming;Zhile Yang

  • Compact real-valued teaching-learning based optimization with the applications to neural network training

    Zhile Yang;Kang Li;Yuanjun Guo;Haiping Ma

Frequent Co-Authors

Kang Li
Kang Li University of Leeds
Minrui Fei
Minrui Fei Shanghai University
Huiyu Zhou
Huiyu Zhou University of Leicester
Wei Feng
Wei Feng Tianjin University
Dongsheng Yang
Dongsheng Yang Eindhoven University of Technology
Monjur Mourshed
Monjur Mourshed Cardiff University
Jiubin Tan
Jiubin Tan Harbin Institute of Technology
Peter J. Fleming
Peter J. Fleming University of Sheffield
Jing Liang
Jing Liang Zhengzhou University
Xiufan Liu
Xiufan Liu Yangzhou University

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