TUNING OF FUZZY MODELS BY FUZZY NEURAL NETWORKS

It is relatively easy to construct a rough fuzzy model with expert knowledge. It is difficult, however, to fine-tune the parameters of the fuzzy model in order to get improved behavior. For the purpose of tackling this problem, we propose a fuzzy neural network model. The proposed model utilizes a prior expert knowledge for target systems, and embodies fuzzy models which consist of fuzzy rules whose antecedent and consequent are fuzzy sets. The model is equipped with a fuzzy inferencing and tuning mechanism for model parameters by learning. It allows us to tune such parameters of fuzzy models as linguistic terms and relative rule importance. In addition, to show its applicability, we perform some experiments and present the results.