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文章基本信息

  • 标题:The Algorithms Optimization of Artificial Neural Network Based on Particle Swarm
  • 本地全文:下载
  • 作者:Yang Xin-quan
  • 期刊名称:The Open Cybernetics & Systemics Journal
  • 电子版ISSN:1874-110X
  • 出版年度:2014
  • 卷号:8
  • 期号:1
  • 页码:519-524
  • DOI:10.2174/1874110X01408010519
  • 出版社:Bentham Science Publishers Ltd
  • 摘要:

    As a new kind of swarm intelligence algorithm, particle swarm optimization (PSO) algorithm can be calculated conveniently to achieve fast convergence and good convergence performance advantages. However, it shows shortcoming of falling into local extreme point. In this paper, a harmony search algorithm was used to improve PSO. Harmony Search Algorithm, as a new optimization algorithm, presents a good global search performance. By examining four standard test functions, the accuracy of convergence speed or convergence using improved PSO harmony search algorithm was validated.

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