INDUCTION OF FUZZY RULES AND MEMBERSHIP FUNCTIONS FROM TRAINING EXAMPLES

Most fuzzy controllers and fuzzy expert systems must predefine members hip functions and fuzzy inference rules to map numeric data into lingu istic variable terms and to make fuzzy reasoning work. In this paper, we propose a general learning method as a framework for automatically deriving membership functions and fuzzy if-then rules from a set of gi ven training examples to rapidly build a prototype fuzzy expert system . Based on the membership functions and the fuzzy rules derived, a cor responding fuzzy inference procedure to process inputs is also develop ed.