A FUZZY NEURAL NETWORK MODEL FOR FUZZY INFERENCE AND RULE TUNING
Keon Myung Lee, DONG-HOON KWANG, HYUNG LEEK WANG · International Journal of Uncertainty Fuzziness and Knowledge-Based Systems · 1994
It is relatively easy to create rough fuzzy rules for a target system. However, it is time-consuming and difficult to fine-tune them for improving their behavior. Meanwhile, in the process of fuzzy inference the defuzzification operation takes most of the inferencing time. In this paper, we propose a fuzzy neural network model which makes it possible to tune fuzzy rules by employing neural networks and reduces the burden of defuzzification operation. In addition, to show the applicability of the proposed model we perform an experiment and present its result.