• DocumentCode
    2542836
  • Title

    Class of weak uni-norm operators and aggregation of fuzzy rules

  • Author

    Yager, Ronald R. ; Rybalov, Alexander

  • Author_Institution
    Machine Intelligence Inst., Iona Coll., New Rochelle, NY, USA
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    424
  • Lastpage
    428
  • Abstract
    We have demonstrated that strong uni-norm aggregation operators belong to the class of weak triangular norm operators. The new class of operators called weak uni-norm operators was introduced by relaxing condition of associativity of uni-norm operators. This class includes linear weighted averaging of uni-norm operators. Resulting weights are fixed and, thus, this type of aggregation can be used for constructing a fuzzy system with desired properties. A particular application involving linear self-identity operators for defining weights of weak uni-norms was considered, and it was shown that the latter provide additional leverage in fuzzy system modeling technology
  • Keywords
    fuzzy set theory; fuzzy systems; fuzzy rule aggregation; fuzzy set theory; fuzzy system modeling; linear self-identity operators; linear weighted averaging; strong uni-norm aggregation operators; uni-norm operator associativity; weak triangular norm operators; weak uni-norm operators; Boundary conditions; Educational institutions; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Gallium nitride; Machine intelligence; Modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 2000. NAFIPS. 19th International Conference of the North American
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    0-7803-6274-8
  • Type

    conf

  • DOI
    10.1109/NAFIPS.2000.877466
  • Filename
    877466