• DocumentCode
    2305302
  • Title

    Gaussion Mutation Particle Swarm Optimization with Dynamic Adaptation Inertia Weight

  • Author

    Lili Li ; Xingshi He

  • Author_Institution
    Dept. of Math., Xi´an Polytech. Univ., Xi´an, China
  • Volume
    4
  • fYear
    2009
  • fDate
    19-21 May 2009
  • Firstpage
    454
  • Lastpage
    459
  • Abstract
    An improved PSO with decreasing inertia weight is proposed in this paper, which is different from the inertia weight of standard PSO. In addition, a new social component instead of the old one to make more explore and a tiny Gauss perturbation joined in the position equation to help maintain swarm diversity. Four standard test functions with asymmetric initial range settings are used to prove its validity. Experimental results verify its superiority both in convergent speed and solution precision. Conclusions are drawn in the end.
  • Keywords
    Gaussian processes; optimisation; Gauss perturbation; Gaussion mutation; dynamic adaptation inertia weight; particle swarm optimization; position equation; standard test functions; Cultural differences; Equations; Gaussian processes; Genetic mutations; Mathematics; Neural networks; Particle swarm optimization; Software engineering; Software standards; Testing; Gaussion mutation; Particle Swarm Optimization; inertia weight;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, 2009. WCSE '09. WRI World Congress on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-0-7695-3570-8
  • Type

    conf

  • DOI
    10.1109/WCSE.2009.24
  • Filename
    5319596