FUZZY EXPERT SYSTEM BASED ON ROUGH SETS AND ITS APPLICATION TO MEDICAL DIAGNOSIS
We propose a new method of reducing information systems by considering the classification given by experts, and a method of constructing a fuzzy expert system is described by introducing fuzzy intervals represented as fuzzification of attribute values. As an example, a fuzzy expert system for medical diagnosis is built using fuzzy inference rules. There are 367 fuzzy if-then rules constructed by the lower approximations which show consistency of the given data and the classification given by experts.
rough sets classification fuzzy inference fuzzy if-then rules