Financial security evaluation of the electric power industry in China based on a back propagation neural network optimized by genetic algorithm
作者: Wei SunYanfeng Xu
作者单位: 1Department of Economics and Management, North China Electric Power University Baoding, 071003, China
刊名: Energy, 2016, Vol.101 , pp.366-379
来源数据库: Elsevier Journal
DOI: 10.1016/
关键词: Financial security evaluationPower industryGenetic algorithmBack propagation neural network
英文摘要: Abstract(#br)Recently security issues like investment and financing in China's power industry have become increasingly prominent, bringing serious challenges to the financial security of the domestic power industry. Thus, it deserves to develop financial safety evaluation towards the Chinese power industry and is of practical significance. In this paper, the GA (genetic algorithm) is used to optimize the connection weights and thresholds of the traditional BPNN (back propagation neural network) so the new model of BPNN based on GA is established, hereinafter referred to as GA-BPNN (back propagation neural network based on genetic algorithm). Then, an empirical example of the electric power industry in China during the period 2003–2010 was selected to verify the proposed algorithm. By...
全文获取路径: Elsevier  (合作)
影响因子:3.651 (2012)

  • security 可靠性
  • industry 工业
  • genetic 遗传的
  • algorithm 算法
  • China 中国
  • neural 神经系统的
  • evaluation 评价
  • power 功率
  • propagation 传播
  • optimized 最佳的