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A fuzzy logic system for expert systems

Published online by Cambridge University Press:  27 February 2009

Te-Chuan Chang ,
C. William Ibbs  and
Keith C. Crandall
Te-Chuan Chang
Affiliation:
Department of Civil Engineering, University of California, Berkeley, CA 94720, U.S.A.
C. William Ibbs
Affiliation:
Department of Civil Engineering, University of California, Berkeley, CA 94720, U.S.A.
Keith C. Crandall
Affiliation:
Department of Civil Engineering, University of California, Berkeley, CA 94720, U.S.A.
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Abstract

Using the theory of fuzzy sets, this paper develops a fuzzy logic reasoning system as an augmentation to a rule-based expert system to deal with fuzzy information. First, fuzzy set theorems and fuzzy logic principles are briefly reviewed and organized to form a basis for the proposed fuzzy logic system. These theorems and principles are then extended for reasoning based on knowledge base with fuzzy production rules. When an expert system is augmented with the fuzzy logic system, the inference capability of the expert system is greatly expanded; and the establishment of a rule-based knowledge base becomes much easier and more economical. Interpretations of the system’s power and possible future research directions conclude the paper.

Type
Research Article
Information
AI EDAM , Volume 2 , Issue 3 , August 1988 , pp. 183 - 193
Copyright
Copyright © Cambridge University Press 1988

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