Acta Physica Sinica, Volume. 69, Issue 10, 100701-1(2020)

A hybrid model for photovoltaic power prediction of both convolutional and long short-term memory neural networks optimized by genetic algorithm

Chen-Yang Wang1, Qian-Qian Duan1, Kai Zhou1, Jing Yao1, Min Su1, Yi-Chao Fu1, Jun-Yang Ji1, Xin Hong1, Xue-Qin Liu1、*, and Zhi-Yong Wang2、*
Author Affiliations
  • 1Chongqing Key Laboratory of Green Energy Materials Technology and Systems, School of Science, Chongqing University of Technology, Chongqing 400054, China
  • 2School of Physical Science and Technology, Southwest University, Chongqing 400715, China
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    Chen-Yang Wang, Qian-Qian Duan, Kai Zhou, Jing Yao, Min Su, Yi-Chao Fu, Jun-Yang Ji, Xin Hong, Xue-Qin Liu, Zhi-Yong Wang. A hybrid model for photovoltaic power prediction of both convolutional and long short-term memory neural networks optimized by genetic algorithm[J]. Acta Physica Sinica, 2020, 69(10): 100701-1

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    Paper Information

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    Received: Dec. 20, 2019

    Accepted: --

    Published Online: Nov. 30, 2020

    The Author Email: Zhi-Yong Wang (zywang@swu.edu.cn)

    DOI:10.7498/aps.69.20191935

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