Fuzzy reasoning based on generalized fuzzy If‐Then rules | Zendy

Xu Yang | Zendy; Liu Jun | Zendy; Ruan Da | Zendy; Li Wenjiang | Zendy

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Fuzzy reasoning based on generalized fuzzy If‐Then rules

Author(s) -

Xu Yang,

Liu Jun,

Ruan Da,

Li Wenjiang

Publication year - 2002

Publication title -

international journal of intelligent systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.291

H-Index - 87

eISSN - 1098-111X

pISSN - 0884-8173

DOI - 10.1002/int.10056

Subject(s) - mathematics , type 2 fuzzy sets and systems , extension (predicate logic) , fuzzy logic , fuzzy set operations , fuzzy classification , fuzzy number , type (biology) , relation (database) , defuzzification , artificial intelligence , fuzzy rule , neuro fuzzy , binary number , fuzzy associative matrix , fuzzy set , computer science , data mining , fuzzy control system , arithmetic , programming language , ecology , biology

This paper focuses on a fuzzy reasoning method based on a generalized If‐Then rule. Firstly, the antecedent and the consequent of an If‐Then rule are considered and expressed as a component of a kind of binary L ‐type fuzzy relation on the product of the universes of discourse and the range of definition for a certain fuzzy attribute. Then a generalized extension principle based on this L ‐type fuzzy relation (FR‐GEP) is constructed. Moreover, the paper gives a detailed description of this generalized If‐Then rule using 20 well‐known common implication operators in the framework of the composition of L ‐type fuzzy relations. Consequently, an L ‐type binary fuzzy reasoning method based on this generalized If‐Then rule is established according to FR‐GEP. © 2002 Wiley Periodicals, Inc.

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