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  • 标题:Short-Term Wind Power Forecasting Model based on ICA-BP Neural Network
  • 本地全文:下载
  • 作者:Zi-Cheng Lan ; Yuan-Biao Zhang ; Jing Zhang
  • 期刊名称:Computer and Information Science
  • 印刷版ISSN:1913-8989
  • 电子版ISSN:1913-8997
  • 出版年度:2014
  • 卷号:8
  • 期号:1
  • 页码:1
  • DOI:10.5539/cis.v8n1p1
  • 语种:English
  • 出版社:Canadian Center of Science and Education
  • 摘要:It’s of great significance for wind power integration into grid to forecast wind power. Based on forecasting wind power by BP neural network, the article introduces global optimization algorithm, Imperialist Competitive Algorithm (ICA) to provide optimized initial weights of BP neural network. Thus, it can overcome the entrapment in local optical optimum of BP neural network. Compared with BP neural network, it is found that the performances of ICA-BP neural network, which are training, testing and forecasting of wind power, are much better.
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