• DocumentCode
    2639261
  • Title

    Study on Convergent Fuzzy Particle Swarm Optimization and Performance Analysis

  • Author

    Meng, Xuelei ; Jia, Limin

  • Author_Institution
    State Key Lab. of Rail Traffic Control & Safety, Beijing Jiaotong Univ., Beijing
  • fYear
    2008
  • fDate
    18-20 June 2008
  • Firstpage
    458
  • Lastpage
    458
  • Abstract
    Fuzzy particle swarm optimization (FPSO) has shown its great searching ability and high computing precision, while it can not assure the algorithm is convergent. In this paper, a new kind of FPSO is proposed, called convergent fuzzy particle swarm optimization (CFPSO), employing the convergent gene. It differs from normal FPSO in that a convergent gene is introduced in the velocity equation. And it differs from convergent particle swarm optimization (CPSO) in that it employs the fuzzy membership function in the velocity equation. The CFPSO performance is evaluated with four popular benchmark functions, compared with FPSO, CPSO and standard PSO. The experimental results show the model is well built and better performance can be gained with the new optimization algorithm.
  • Keywords
    convergence; fuzzy set theory; genetic algorithms; particle swarm optimisation; search problems; convergent fuzzy particle swarm optimization; convergent gene; fuzzy membership function; performance analysis; searching ability; velocity equation; Computational intelligence; Equations; Fuzzy control; High performance computing; Laboratories; Particle swarm optimization; Performance analysis; Rail transportation; Railway safety; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
  • Conference_Location
    Dalian, Liaoning
  • Print_ISBN
    978-0-7695-3161-8
  • Electronic_ISBN
    978-0-7695-3161-8
  • Type

    conf

  • DOI
    10.1109/ICICIC.2008.519
  • Filename
    4603647