Rule base reduction methods for fuzzy systems

Alexander Gegov

doi:10.1007/978-3-540-38885-2_3

Rule base reduction methods for fuzzy systems

Alexander Gegov

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Abstract

The first group of methods for rule base reduction are aimed at removing less significant or merging similar linguistic values [67, 68]. For simplicity, this group of methods and all other methods in the current chapter will be illustrated by integer tables such that the linguistic values of the inputs are coded by integers whereas the outputs are either skipped as irrelevant or presented in a general form.

Original language	English
Title of host publication	Complexity Management in Fuzzy Systems
Subtitle of host publication	A Rules Base Compression Approach
Publisher	Springer
Chapter	6
Pages	17-31
Number of pages	15
Edition	1st
ISBN (Electronic)	9783540388852
ISBN (Print)	3540388834, 9783540388838
DOIs	https://doi.org/10.1007/978-3-540-38885-2_3 https://doi.org/10.1007/978-3-540-38885-2
Publication status	Published - 2 Jun 2007

Publication series

Name	Studies in Fuzziness and Soft Computing
Volume	211
ISSN (Print)	1434-9922
ISSN (Electronic)	1860-0808

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Rule base reduction methods for fuzzy systems

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