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Convergence property and parametersselection strategy base on differential evolution of PSO

Pan Guan-yu1，Liu Da-you1，Dou Quan-sheng2，Liu Xiao-hua2   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012, China; 2.School of Information and Electronics Engineering, Shandong Institute of Business and Technology, Yantai 264005, China
  • Received:2006-06-21 Revised:2006-08-29 Online:2007-07-01 Published:2007-07-01
  • Contact: Liu Da-you

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Abstract: It was modified and completed that the previous research result on PSO convergence property and proposed a new strategy on parameter selection which did not depend on expert experience. It transformed the parameterselection problem into functional optimization problem by creating a function of the PSO property parameters. The result is also very promising in finding the optimal parameters of PSO by differential evolution.

Key words: artificial intelligence, particle swarm optimization, convergence property, parametersselection, differential evolution

CLC Number: 

  • TP182
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