• DocumentCode
    2694622
  • Title

    Training type-2 Fuzzy System by particle swarm optimization

  • Author

    Al-Jaafreh, Moha Med O ; Al-Jumaily, Adel A.

  • Author_Institution
    Univ. of Technol., Sydney
  • fYear
    2007
  • fDate
    25-28 Sept. 2007
  • Firstpage
    3442
  • Lastpage
    3446
  • Abstract
    Many intelligent techniques were established during last decades to handle nonlinear, multimode, noisy, nondifferentiable problems and to obtain optimum solution(s). This paper presents improving and implementations for two recently intelligent techniques; type-2 fuzzy system (T2 FS) and particle swarm optimization (PSO) and presents a new method to optimize parameters of the primary membership functions of T2 FS by PSO to improve the performance and increase the accuracy of T2 FS model. The implementation of the suggested method on mean blood pressure estimation has very successful rate.
  • Keywords
    fuzzy set theory; particle swarm optimisation; intelligent techniques; membership functions; particle swarm optimization; type-2 fuzzy system; Evolutionary computation; Fuzzy systems; Particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-1339-3
  • Electronic_ISBN
    978-1-4244-1340-9
  • Type

    conf

  • DOI
    10.1109/CEC.2007.4424917
  • Filename
    4424917