• DocumentCode
    2590273
  • Title

    Improved Opposition-Based PSO for Feedforward Neural Network Training

  • Author

    Rashid, Muhammad ; Baig, Abdul Rauf

  • Author_Institution
    Nat. Univ. of Comput. & Emerging Sci., Islamabad, Pakistan
  • fYear
    2010
  • fDate
    21-23 April 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this study we present an improved opposition- based PSO and apply it to feedforward neural network training. The improved opposition-based PSO utilizes opposition-based initialization, opposition-based generation jumping and opposition-based velocity calculation. The opposition-based PSO is first tested on some unimodal and multimodal problems and its performance is compared with standard PSO. We then test the performance of the improved opposition-based PSO for training feedforward neural network and also present a comparison with standard PSO.
  • Keywords
    feedforward neural nets; particle swarm optimisation; feedforward neural network; opposition-based generation jumping; opposition-based velocity calculation; particle swarm optimization; Clamps; Cognition; Computer networks; Convergence; Cultural differences; Equations; Feedforward neural networks; Neural networks; Particle swarm optimization; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Applications (ICISA), 2010 International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-5941-4
  • Electronic_ISBN
    978-1-4244-5943-8
  • Type

    conf

  • DOI
    10.1109/ICISA.2010.5480380
  • Filename
    5480380