• DocumentCode
    1675507
  • Title

    A method for structure identification in complete rule-based fuzzy systems

  • Author

    Pomares, H. ; Rojas, I. ; González, J. ; Prieto, A.

  • Author_Institution
    Fac. de Ciencias, Granada Univ., Spain
  • Volume
    1
  • fYear
    2001
  • fDate
    6/23/1905 12:00:00 AM
  • Firstpage
    376
  • Lastpage
    379
  • Abstract
    This paper presents a reliable method to obtain the structure of a complete rule-based fuzzy system for a specific approximation accuracy of the training data, i.e. it can decide which input variables must be taken into account in the fuzzy system and how many membership functions are needed in every selected input variable in order to reach the approximation target with the minimum number of parameters
  • Keywords
    approximation theory; fuzzy systems; identification; knowledge based systems; learning (artificial intelligence); uncertainty handling; approximation target; complete rule-based fuzzy systems; fuzzy membership functions; input variable; input variables; minimum parameter number; structure identification; training data approximation accuracy; Bibliographies; Computer architecture; Electronic mail; Fuzzy control; Fuzzy sets; Fuzzy systems; Input variables; Optimization methods; Topology; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2001. The 10th IEEE International Conference on
  • Conference_Location
    Melbourne, Vic.
  • Print_ISBN
    0-7803-7293-X
  • Type

    conf

  • DOI
    10.1109/FUZZ.2001.1007327
  • Filename
    1007327