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2019 | OriginalPaper | Chapter

Inference Methods for One Class of Systems with Many Fuzzy Inputs

Authors : Vasiliy Sinuk, Maxim Panchenko

Published in: Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

The paper presents the inference methods for fuzzy systems of Mamdani type, which, for many fuzzy inputs and for any t-norms, are implemented with polynomial computational complexity. Center of sums and the discrete version of the center of gravity methods are applied for the rule base at the defuzzification stage. The network structures of the systems corresponding to these methods are given.

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Metadata
Title
Inference Methods for One Class of Systems with Many Fuzzy Inputs
Authors
Vasiliy Sinuk
Maxim Panchenko
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-30763-9_21

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