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Rule Base Reduction Methods for Fuzzy Systems

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 211))

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.

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© 2007 Springer

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Gegov, A. (2007). Rule Base Reduction Methods for Fuzzy Systems. In: Complexity Management in Fuzzy Systems. Studies in Fuzziness and Soft Computing, vol 211. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-38885-2_3

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  • DOI: https://doi.org/10.1007/978-3-540-38885-2_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-38883-8

  • Online ISBN: 978-3-540-38885-2

  • eBook Packages: EngineeringEngineering (R0)

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