Fuzzy Rules Generation Using the LVQ


The Transactions of the Korea Information Processing Society (1994 ~ 2000), Vol. 6, No. 4, pp. 988-998, Apr. 1999
10.3745/KIPSTE.1999.6.4.988,   PDF Download:

Abstract

This paper is to investigate the method of reducing the number of fuzzy rules with the help of LVQ. A large number of training patterns usually leads to a large set of fuzzy rules that require a large computer memory and take a long time to perform classification. So, in order to solve these problems, it is necessary to study to minimize the number of fuzzy rules. However, so as to minimize the performance degradation resulting from the reduction of fuzzy rules, fuzzy rules are generated after training the high-quality initial reference pattern. Through the simulation we confirm that the proposed method is very effective.


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Cite this article
[IEEE Style]
L. N. II, J. G. Gyu, L. H. Kyu, "Fuzzy Rules Generation Using the LVQ," The Transactions of the Korea Information Processing Society (1994 ~ 2000), vol. 6, no. 4, pp. 988-998, 1999. DOI: 10.3745/KIPSTE.1999.6.4.988.

[ACM Style]
Lee Nam II, Jang Gwang Gyu, and Lim Han Kyu. 1999. Fuzzy Rules Generation Using the LVQ. The Transactions of the Korea Information Processing Society (1994 ~ 2000), 6, 4, (1999), 988-998. DOI: 10.3745/KIPSTE.1999.6.4.988.