Acquisition of fuzzy knowledge by NN and GA-A survey of the fusion and union methods proposed in Japan

Fuzzy control is an effective method widely employed in the complex control field. However, in the fuzzy control, the adjustment (tuning) of the shape of membership functions and the acquisition of fuzzy rules is still a very active research field. To solve the tuning problem, a number of fusion/union methods using neural networks (NN) or genetic algorithms (GA) have been proposed. By scanning through these methods, we find that these methods are roughly divided into some categories depending on the grade of fusion/union between fuzzy models and NN, GA. In this papers, the fusion/union models are discussed and their applications in the field of control are explained