• DocumentCode
    3244766
  • Title

    Analogous fuzzy rule-based expert systems

  • Author

    Vadiee, N. ; Mohammad, Rahim ; Akbarzadeh, T.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., New Mexico Univ., Albuquerque, NM
  • Volume
    3
  • fYear
    1996
  • fDate
    8-11 Sep 1996
  • Firstpage
    1852
  • Abstract
    In this paper, the concepts of primary fuzzy term sets and basis fuzzy sets are introduced. In order to remedy the problem of context in fuzzy reasoning environments, it is shown that a base logic, such as the main fuzzy logic paradigm proposed by Zadeh, could be employed in conjunction with three proposed primary fuzzy term sets, to model new logical operations and primitives. The proposed flexible structure introduced for fuzzy reasoning paradigms, called “soft fuzzy reasoning paradigm”, provides the methodology for the implementation of all the known parameterized fuzzy reasoning paradigms. Canonical and base canonical fuzzy rule-based expert systems are introduced and employed to address the definition of analogous fuzzy systems. Three types of analogous fuzzy systems are discussed. As a problem case, two physically different systems such as a flexible robot and a heating slab which fall under type one of analogous systems, are discussed. Conditions for the transfer of knowledge across two analogous fuzzy systems are mentioned
  • Keywords
    expert systems; fuzzy logic; fuzzy set theory; fuzzy systems; inference mechanisms; knowledge representation; analogous fuzzy systems; flexible robot; fuzzy logic; fuzzy reasoning; fuzzy rule-based expert systems; fuzzy set theory; heating slab; knowledge transfer; Context modeling; Expert systems; Flexible structures; Fuzzy logic; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Heating; Hybrid intelligent systems; Robots;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-7803-3645-3
  • Type

    conf

  • DOI
    10.1109/FUZZY.1996.552679
  • Filename
    552679