Constructing hierarchical fuzzy rule bases for classification

Gedeon, T., Wong, K.W. and Tikk, D. (2001) Constructing hierarchical fuzzy rule bases for classification. In: The 10th IEEE International Conference on Fuzzy Systems, 2001, 2-5 Dec. 2001, Melbourne, Victoria pp. 1388-1391.

Abstract

Fuzzy rule based systems have been very popular in many control applications. However, when fuzzy control systems are used in real problems, many rules may be required. The number of rules required depends on the number of inputs and the number of fuzzy linguistic terms used. This exponential explosion of fuzzy rules can take too much computing time to solve any but the simplest problems. This paper proposes a hierarchical fuzzy system that partitions a problem for more efficient computation. The hierarchical fuzzy rule base algorithm constructs rules from data for the purpose of performing fuzzy classification. Illustration examples are also generated and the results show that this hierarchical fuzzy system can be successfully used for classification applications.

Item Type:	Conference Paper
Murdoch Affiliation(s):	School of Information Technology
Publisher:	IEEE
Copyright:	© 2001 IEEE
Notes:	Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
URI:	http://researchrepository.murdoch.edu.au/id/eprint/1019

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