A Classifier Based on Neuro-Fuzzy Inference System Ernest

Czogala; Jacek Leski; Yoichi Hayashi

doi:10.20965/jaciii.1999.p0282

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JACIII Vol.3 No.4 pp. 282-288

doi: 10.20965/jaciii.1999.p0282

(1999)

Paper:

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A Classifier Based on Neuro-Fuzzy Inference System Ernest

Czogala^, Jacek Leski^, and Yoichi Hayashi^**

^*Institute of Electronics, Technical University of Silesia Akademicka 16, 44-101 Gliwice, Poland

^**Department of Computer Science, Meiji University 1-1-1 Higashimita, Tama-ku, Kawasaki 214-8571, Japan

Received:

January 10, 1999

Accepted:

June 21, 1999

Published:

August 20, 1999

Keywords:

Neuro-fuzzy inference system, If-then rules, Fuzzy classifier, Pattern recognition

Abstract

In this paper a new classifier based on fuzzy inference system has been described. The novelty of the classifier consists in the moving fuzzy consequent in if-then rules and in selection method of target values for classifier outputs minimizing the number of false classifications. The location of fuzzy set in conclusion is determined by a linear combination of system inputs. The method of classifier construction for two classes and an extension for a greater number of classes has been presented. The tests of the new classifier are carried out on the basis of the data bases known from literature: forensic glass and iris.

Cite this article as:

Czogala, Jacek Leski, and Yoichi Hayashi, “A Classifier Based on Neuro-Fuzzy Inference System Ernest,” J. Adv. Comput. Intell. Intell. Inform., Vol.3, No.4, pp. 282-288, 1999.

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This article is published under a Creative Commons Attribution-NoDerivatives 4.0 International License.

A Classifier Based on Neuro-Fuzzy Inference System Ernest

Czogala*, Jacek Leski*, and Yoichi Hayashi**

Czogala^, Jacek Leski^, and Yoichi Hayashi^**