• DocumentCode
    686316
  • Title

    Designing mamdani type fuzzy rule using a collaborative FCM scheme

  • Author

    Chin-Teng Lin ; Prasad, M. ; Jyh-Yeong Chang

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • fYear
    2013
  • fDate
    6-8 Dec. 2013
  • Firstpage
    279
  • Lastpage
    282
  • Abstract
    This paper presents a new approach for generating fuzzy rules for fuzzy inference system by using collaborative fuzzy c-mean (CFCM). In order to do any mode of integration between datasets, there is a need to define the common feature between datasets by using some kind of collaborative process and also need to preserve the privacy and security at higher levels. This collaboration process gives a common structure between datasets which helps to define an appropriate number of rules for structural learning and also improve the accuracy of the system modeling. This all consideration bring the concept of collaborative fuzzy rule generation process with a quality measuring.
  • Keywords
    fuzzy reasoning; learning (artificial intelligence); pattern clustering; CFCM; Mamdani type fuzzy rule; collaborative FCM scheme; collaborative fuzzy c-mean; collaborative fuzzy rule generation process; fuzzy inference system; structural learning; system modeling; Man machine systems; Radio access networks; collaboration; fuzzy c-means; fuzzy inference system; privacy and security; structural learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Theory and Its Applications (iFUZZY), 2013 International Conference on
  • Conference_Location
    Taipei
  • Type

    conf

  • DOI
    10.1109/iFuzzy.2013.6825450
  • Filename
    6825450