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An improved particle swarm optimization with re-initialization mechanism

  • Jie Guo*
  • , Sheng Jing Tang
  • *此作品的通讯作者
  • Beijing Institute of Technology

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

An improved Particle Swarm Optimization with reinitialization mechanism, which is based on the estimation of the varieties and activities of the particles, is proposed to balance the global search ability of the Standard Swarm Optimization (SPSO). Firstly the motion behavior of single particle is discussed, including the motion mode, convergence and the relationship between motion characteristic and the performance of SPSO. Then, a new variable named "steplength" is employed to represent the variety and activity of the particle population. The group of particles which satisfied the re-initialization conditions will be reinitialized in probability so that the variety and activity of the particle population can be hold in a reasonable level. Experiment results indicate that the improved Particle Swarm Optimization proposed in this paper has better performance compared with the other three PSO algorithms.

源语言英语
主期刊名2009 International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2009
437-441
页数5
DOI
出版状态已出版 - 2009
活动2009 International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2009 - Hangzhou, Zhejiang, 中国
期限: 26 8月 200927 8月 2009

出版系列

姓名2009 International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2009
1

会议

会议2009 International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2009
国家/地区中国
Hangzhou, Zhejiang
时期26/08/0927/08/09

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