THREE-PARAMETER FUZZY ARITHMETIC APPROXIMATION OF L-R FUZZY NUMBERS FOR FUZZY NEURAL NETWORKS
Hsiao‐Fan Wang, Ching-Yi Kuo · International Journal of Uncertainty Fuzziness and Knowledge-Based Systems · 2006
In this study, we proposed an alternative operation of fuzzy arithmetic on L-R fuzzy numbers by three parameters of mode, left spread and right spread. Then, based on this approximation method, a new learning algorithm of a fully fuzzified neural network was developed in which the L-R fuzzy numbers were considered as the fuzzy signals. While the forward operations of fuzzy signals were based on the proposed three-parameter fuzzy arithmetic approximation method, the backward learning adopted a back-propagation learning procedure with a measurable error function. The learning algorithm was illustrated by an example of the recognition of fuzzy IF-THEN rules. The simulation result showed that the proposed approximation method used in such learning model was efficient and accurate.