• DocumentCode
    1661758
  • Title

    Fuzzy modeling by hyperbolic fuzzy k-means clustering

  • Author

    Watanabe, Norio

  • Author_Institution
    Dept. of Ind. & Syst. Eng., Chuo Univ., Tokyo, Japan
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1528
  • Lastpage
    1531
  • Abstract
    A parameterized Takagi-Sugeno´s model is proposed by introducing the classification function used in the hyperbolic fuzzy k-means method, and an identification procedure of this model is presented by applying the hyperbolic fuzzy k-means
  • Keywords
    fuzzy set theory; identification; nonlinear systems; pattern clustering; Takagi-Sugeno model; fuzzy clustering; fuzzy model; fuzzy set theory; hyperbolic fuzzy k-means method; identification; nonlinear system; parametrization; Clustering methods; Equations; Fuzzy sets; Fuzzy systems; Input variables; Principal component analysis; Systems engineering and theory; Takagi-Sugeno model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7280-8
  • Type

    conf

  • DOI
    10.1109/FUZZ.2002.1006733
  • Filename
    1006733
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1661758