Fuzzy rules extraction by a hybrid method for pattern classification

A method based on the concepts of genetic algorithm (GA) and SVD-QR method is proposed to construct an appropriate fuzzy system for pattern classification. In this method, an individual of the population in the GA is used to determine a fuzzy partition such that some rough fuzzy sets of each input variable are obtained. The SVD-QR method is used to extract significant fuzzy rules from the rule base of the defined fuzzy system. Furthermore, a fitness function in the GA is considered to guide the search procedure to select an appropriate fuzzy system such that the number of incorrectly, classified patterns and the number of fuzzy rules are minimized. Finally, a classification problem is considered to illustrate the effectiveness of the proposed method