• DocumentCode
    2682098
  • Title

    A Fuzzy Inference Method for Systems with Large Number of Rules

  • Author

    Bustan, Danyal ; Moodi, Hoda ; Pariz, Naser ; Azmoodeh, Nika

  • Author_Institution
    Ferdowsi Univ. of Mashhad
  • fYear
    2006
  • fDate
    3-6 June 2006
  • Firstpage
    397
  • Lastpage
    402
  • Abstract
    In this paper, a new fuzzy inference method which is suitable for systems with large number of rules, is proposed. As we know, there are two well-known fuzzy inference systems, Mamdani and TSK. Each one has its own drawbacks and advantages but both of them have been encountered with problem while tuning their parameters especially when there is large number of rules in the system. Mamdani type systems faced to a huge amount of calculation and TSK type faced to large number of parameters. In our proposed method a combination of these two systems, is used. So it has small number of parameters for tuning as Mamdani has and it is as fast as TSK. We called this system extended TSK because it is based upon it
  • Keywords
    fuzzy logic; fuzzy reasoning; fuzzy systems; Mamdani type systems; extended TSK type; fuzzy inference method; fuzzy modelling; Application software; Fuzzy logic; Fuzzy sets; Fuzzy systems; Humans; Input variables;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 2006. NAFIPS 2006. Annual meeting of the North American
  • Conference_Location
    Montreal, Que.
  • Print_ISBN
    1-4244-0363-4
  • Electronic_ISBN
    1-4244-0363-4
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2006.365442
  • Filename
    4216835