Fuzzy Rule Identification System using Artificial Neural Networks


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 2, No. 2, pp. 209-214, Mar. 1995
10.3745/KIPSTE.1995.2.2.209,   PDF Download:

Abstract

It is very hard to identify the fuzzy rules and tune the membership functions of the fuzzy reasoning in fuzzy systems modeling. We propose a method which canautomatically identify the fuzzy rules and tune the membership functions of fuzzy reasoning simultaneously using artificial neural. In this model, fuzzy rules are identified by backpropagation algorithm. The feasibility of the method is simulated by a simple robot manipulator.


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Cite this article
[IEEE Style]
J. M. Suk and C. D. Chul, "Fuzzy Rule Identification System using Artificial Neural Networks," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 2, no. 2, pp. 209-214, 1995. DOI: 10.3745/KIPSTE.1995.2.2.209.

[ACM Style]
Jang Moon Suk and Chang Duk Chul. 1995. Fuzzy Rule Identification System using Artificial Neural Networks. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 2, 2, (1995), 209-214. DOI: 10.3745/KIPSTE.1995.2.2.209.