• DocumentCode
    509171
  • Title

    Adaptive Population Differentiation PSO Algorithm

  • Author

    Yang Junjie ; Xue, Liqin

  • Author_Institution
    Sch. of Inf. & Technol., Zhanjiang Normal Univ., Zhanjiang, China
  • Volume
    2
  • fYear
    2009
  • fDate
    21-22 Nov. 2009
  • Firstpage
    388
  • Lastpage
    391
  • Abstract
    In order to solve the problem of easily fall into local optimal solutions, lower convergent precision, slower convergence rates and the poor population diversity, an improved PSO algorithm was proposed in this paper. The diversity was improved by the application of fuzzy clustering method. The sub-populations were classified automatically based on the feature of the population, and the information was exchanged by alliance in among the sub-populations. The simulation results of our improved PSO and indicated that the performance of optimal precision, efficiency and the stability are much better than that of traditional PSO.
  • Keywords
    convergence; fuzzy set theory; particle swarm optimisation; pattern clustering; PSO algorithm; adaptive population differentiation; convergence rate; convergent precision; fuzzy clustering; local optimal solution; population diversity; Acceleration; Clustering algorithms; Clustering methods; Educational institutions; Evolutionary computation; Information science; Information technology; Particle swarm optimization; Particle tracking; Stability; PSO algorithm; diversity; fuzzy clustering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
  • Conference_Location
    Nanchang
  • Print_ISBN
    978-0-7695-3859-4
  • Type

    conf

  • DOI
    10.1109/IITA.2009.379
  • Filename
    5369593