Development of a Rule-based Expert System with Fuzzy Sets and Fuzzy Logic

We propose in this paper to model of a rule based expert systems using the techniques of Fuzzy sets and Fuzzy logic. In the real world problem solving is the process of finding a solution when the path leading to that solution is uncertain. The Expert Systems need to have the ability to handle vague associations, for example by accepting the degree of correlations as numerical certainty factors. When the data is incomplete or missing, the only solution is to accept the value “unknown” and proceed to an approximate reasoning with this value. Fuzzy logic provides a framework to model uncertainity, the human way of thinking, reasoning and the perception process. In this paper we proposes a fuzzy rule based expert system is simply an expert system that uses a collection of fuzzy membership functions and rules to solve the uncertainty.