• DocumentCode
    2914147
  • Title

    Introduce a New Inertia Weight for Particle Swarm Optimization

  • Author

    Ememipour, Jafar ; Nejad, M. Mehdi Seyed ; Ebadzadeh, M. Mehdi ; Rezanejad, Javad

  • Author_Institution
    Dept. of Comput. & IT Eng., Azad Univ. of Qazvin, Qazvinjran, China
  • fYear
    2009
  • fDate
    24-26 Nov. 2009
  • Firstpage
    1650
  • Lastpage
    1653
  • Abstract
    PSO has a few parameters to adjust such as inertia weight, velocity and constant factors. Among these parameters, inertia weight is very important and has a great potential to develop. During the last decade, various methods like fuzzy, constant, linear methods were proposed to adjust an inertia weight. This paper proposes a new strategy to calculate inertia weight based on decreasing exponential method. Our method merely uses an iteration to make an inertia weight and it is fast and has highly accurate results rather than other strategies. Our results are tested on well-known benchmarks. Numerical results demonstrated our claim.
  • Keywords
    particle swarm optimisation; PSO; decreasing exponential method; inertia weight; particle swarm optimization; Benchmark testing; Birds; Educational institutions; Genetic mutations; Information technology; Java; Marine animals; Particle swarm optimization; Random number generation; inertia weight; optimization; particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Sciences and Convergence Information Technology, 2009. ICCIT '09. Fourth International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-5244-6
  • Electronic_ISBN
    978-0-7695-3896-9
  • Type

    conf

  • DOI
    10.1109/ICCIT.2009.297
  • Filename
    5369239