• DocumentCode
    2087296
  • Title

    Research on BP algorithm and PSO algorithm in the neural network

  • Author

    Tian Yanbing

  • Author_Institution
    Autom. Eng. Coll., Qingdao Technol. Univ., Qingdao, China
  • fYear
    2010
  • fDate
    29-31 July 2010
  • Firstpage
    2381
  • Lastpage
    2384
  • Abstract
    Application of the basic BP algorithm, Levenberg-Marquardt algorithm and the PSO algorithm in the neural network are compared with each other. For the Iris and Breast Cancer data, the mean time of training, the minimum of training error, the minimum of test error, the mean recognition rate are compared. Characteristics of various algorithms for neural network training are analyzed in this paper, and simulation results show that, BP algorithm has some advantages in the limited time.
  • Keywords
    backpropagation; neural nets; particle swarm optimisation; BP algorithm; Levenberg-Marquardt algorithm; PSO algorithm; neural network; Artificial neural networks; Breast cancer; Feeds; IEEE Press; Particle swarm optimization; Training; BP Network; Levenberg-Marquardt; PSO Algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2010 29th Chinese
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-6263-6
  • Type

    conf

  • Filename
    5572661
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2087296