• DocumentCode
    1612294
  • Title

    Fault Prediction of Power Supply Using SVR Optimized with QPSO

  • Author

    Yang, Sen ; Meng, Chen

  • Author_Institution
    Dept. of Missile Eng., Mech. Eng. Coll., Shijiazhuang, China
  • fYear
    2012
  • Firstpage
    825
  • Lastpage
    827
  • Abstract
    In this paper, fault prediction approach on power supply mixture in the system of certain guidance radar is analyzed and a fault prediction method to optimize SVR based on QPSO is proposed. The QPSO algorithm is introduced, effect factors of SVR capability are analyzed and the steps to optimize SVR parameters based on QPSO are proposed. Experimental results of the fault prediction on power supply mixture show that this approach achieves low percent of error and has achieved the expected results.
  • Keywords
    fault diagnosis; power supplies to apparatus; radar; regression analysis; support vector machines; QPSO-based SVR parameters optimization; SVR capability; fault prediction approach; guidance radar; power supply mixture; Accuracy; Kernel; Power supplies; Prediction algorithms; Predictive models; Support vector machines; Training; Fault Prediction; Power Supply Mixture; QPSO; SVR;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4673-1450-3
  • Type

    conf

  • DOI
    10.1109/ICICEE.2012.219
  • Filename
    6322508