A fuzzy neural network based on fuzzy weighted reasoning method

Abstract

An improved fuzzy weighted reasoning method is presented on the basis of the 'Mamdani' reasoning method. A fuzzy neural network is developed based on the improved fuzzy weighted reasoning method. The training of network weights and optimization of membership functions are conducted using genetic algorithms. Fuzzy rules can be obtained according to the weights of the network. The effectiveness of the network model and the algorithm is examined by simulated experiments.