• DocumentCode
    2315141
  • Title

    Evolutionary optimization of type-2 fuzzy systems based on the level of uncertainty

  • Author

    Hidalgo, D. ; Melin, P. ; Mendoza, O.

  • Author_Institution
    Sch. of Eng., UABC Univ., Tijuana, Mexico
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper we describe an evolutionary method for the optimization of type-2 fuzzy systems based on the level of uncertainty. The proposed evolutionary method produces the best fuzzy inference systems (based on the memberships functions) for particular applications. The optimization of membership functions of the type-2 fuzzy systems is based on the level of uncertainty considering three different cases to reduce the complexity problem of searching the solution space.
  • Keywords
    evolutionary computation; fuzzy systems; inference mechanisms; uncertainty handling; complexity problem; evolutionary optimization; fuzzy inference systems; membership functions; type-2 fuzzy systems; uncertainty level; Artificial neural networks; Fuzzy logic; Fuzzy systems; Input variables; Optimization; Simulation; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-6919-2
  • Type

    conf

  • DOI
    10.1109/FUZZY.2010.5584849
  • Filename
    5584849
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2315141