[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5391/IJFIS.2005.5.1.007

A Study of Construct Fuzzy Inference Network using Neural Logic Network

Lee, Jae-Deuk (Dept. Of Automobile Engineering, Chosun Collage of Science & Technology)
Jeong, Hye-Jin (School of Electronics & Information Engineering, ChonBuk National University)
Kim, Hee-Suk (Dept. Of Multimedia, Asan IT Polytechnic Collage)
Lee, Malrey (School of Electronics & Information Engineering, ChonBuk National University)

Publication Information

International Journal of Fuzzy Logic and Intelligent Systems / v.5, no.1, 2005 , pp. 7-12 More about this Journal

Abstract

This paper deals with the fuzzy modeling for the complex and uncertain nonlinear systems, in which conventional and mathematical models may fail to give satisfactory results. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper. The expert system which introduces fuzzy logic in order to process uncertainties is called fuzzy expert system. The fuzzy expert system, however, has a potential problem which may lead to inappropriate results due to the ignorance of some information by applying fuzzy logic in reasoning process in addition to the knowledge acquisition problem. In order to overcome these problems, We construct fuzzy inference network by extending the concept of reasoning network in this paper. In the fuzzy inference network, the propositions which form fuzzy rules are represented by nodes. And these nodes have the truth values representing the belief values of each proposition. The logical operators between propositions of rules are represented by links. And the traditional propagation rule is modified.

Keywords

Logic Network; Propagation Rules; Fuzzy Inference Network; Search Strategy;

Citations & Related Records

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