• DocumentCode
    2271118
  • Title

    Importance of membership functions: a comparative study on different learning methods for fuzzy inference systems

  • Author

    Lotfi, A. ; Tsoi, A.C.

  • Author_Institution
    Dept. of Electr. Eng., Queensland Univ., Brisbane, Qld., Australia
  • fYear
    1994
  • fDate
    26-29 Jun 1994
  • Firstpage
    1791
  • Abstract
    This paper investigates different adaptive structures for fuzzy inference systems. We examine the effect of membership functions on reasoning process when the number of rules is fixed. Three commonly used membership function shapes have been employed in this study. It has been shown that membership functions have the dominant effect on reasoning process rather than number of rules or inference mechanism. We compare our adaptive membership function scheme with two already proposed by others
  • Keywords
    fuzzy systems; inference mechanisms; learning (artificial intelligence); adaptive structures; fuzzy inference systems; learning methods; membership function shapes; reasoning process; Fuzzy neural networks; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Inference mechanisms; Learning systems; Marine vehicles; Neural networks; Production; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the Third IEEE Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1896-X
  • Type

    conf

  • DOI
    10.1109/FUZZY.1994.343588
  • Filename
    343588