Structure determination in fuzzy modeling: a fuzzy CART approach

This paper presents an innovative approach to the structure determination problem in fuzzy modeling. By using the well-known CART (classification and regression tree) algorithm as a quick preprocess, the proposed method can roughly estimate the structure (numbers of membership functions and number of fuzzy rules, etc.) of a fuzzy inference system; the parameter identification is then carried out by the hybrid learning scheme developed in our previous work. Moreover, the identified fuzzy inference system has the property that the total of firing strengths is always equal to one; this speeds up learning processes and reduces round-off errors.>