World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
54
Citations
12094
World Ranking
4547
National Ranking
606

Best Publications

  • Hybridizing particle swarm optimization with differential evolution for constrained numerical and engineering optimization

    Hui Liu;Zixing Cai;Yong Wang

  • Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction

    Hui Liu;Hui Liu;Hong-qi Tian;Yan-fei Li;Yan-fei Li

  • Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network

    Hui Liu;Xi-wei Mi;Yan-fei Li

  • Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM

    Hui Liu;Xiwei Mi;Yanfei Li

  • Data processing strategies in wind energy forecasting models and applications: A comprehensive review

    Hui Liu;Chao Chen

  • Forecasting models for wind speed using wavelet, wavelet packet, time series and Artificial Neural Networks

    Hui Liu;Hui Liu;Hong Qi Tian;Di Fu Pan;Yan Fei Li;Yan Fei Li

  • A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks

    Hui Liu;Hui Liu;Hui Liu;Chao Chen;Hong-qi Tian;Yan-fei Li;Yan-fei Li

  • A hybrid statistical method to predict wind speed and wind power

    Hui Liu;Hong-Qi Tian;Chao Chen;Yan-fei Li

  • Wind speed forecasting approach using secondary decomposition algorithm and Elman neural networks

    Hui Liu;Hui Liu;Hong-qi Tian;Xi-feng Liang;Yan-fei Li

  • Smart deep learning based wind speed prediction model using wavelet packet decomposition, convolutional neural network and convolutional long short term memory network

    Hui Liu;Xiwei Mi;Yanfei Li

  • Deterministic wind energy forecasting: A review of intelligent predictors and auxiliary methods

    Hui Liu;Chao Chen;Xinwei Lv;Xing Wu

  • Wind speed prediction model using singular spectrum analysis, empirical mode decomposition and convolutional support vector machine

    Xiwei Mi;Hui Liu;Yanfei Li

  • Comparison of four Adaboost algorithm based artificial neural networks in wind speed predictions

    Hui Liu;Hui Liu;Hong-qi Tian;Yan-fei Li;Lei Zhang

  • Smart wind speed deep learning based multi-step forecasting model using singular spectrum analysis, convolutional Gated Recurrent Unit network and Support Vector Regression

    Hui Liu;Xiwei Mi;Yanfei Li;Zhu Duan

  • New wind speed forecasting approaches using fast ensemble empirical model decomposition, genetic algorithm, Mind Evolutionary Algorithm and Artificial Neural Networks

    Hui Liu;Hui Liu;Hongqi Tian;Xifeng Liang;Yanfei Li

  • An experimental investigation of three new hybrid wind speed forecasting models using multi-decomposing strategy and ELM algorithm

    Hui Liu;Xiwei Mi;Yanfei Li

  • A review on multi-objective optimization framework in wind energy forecasting techniques and applications

    Hui Liu;Ye Li;Zhu Duan;Chao Chen

  • A new hybrid ensemble deep reinforcement learning model for wind speed short term forecasting

    Hui Liu;Chengqing Yu;Haiping Wu;Zhu Duan

  • An EMD-recursive ARIMA method to predict wind speed for railway strong wind warning system

    Hui Liu;Hui Liu;Hong qi Tian;Yan fei Li

  • Multi-step wind speed forecasting using EWT decomposition, LSTM principal computing, RELM subordinate computing and IEWT reconstruction

    Yanfei Li;Haiping Wu;Hui Liu

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