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Introduction to fuzzy systems

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

55 Citations (Scopus)

Abstract

The following chapter describes the basic concepts of fuzzy systems and approximate reasoning. The study focuses mainly on fuzzy models based on Zadeh’s compositional rule of inference. The presentation begins with an introduction of fundamental ideas of fuzzy conditional (if-then) rules. A collection of fuzzy if-then rules formulates the so-called knowledge base, which formally represents the knowledge to be processed during approximate reasoning. The subsequent sections present formal definitions related to the compositional rule of inference and approximate reasoning using a knowledge base. Theoretical considerations are supplemented with practical examples of fuzzy systems as the foundation of many modern structures. The description includes fuzzy systems proposed by Mamdani and Assilan, Takagi, Sugeno and Kang, and Tsukamoto.

Original languageEnglish
Title of host publicationStudies in Fuzziness and Soft Computing
PublisherSpringer Verlag
Pages23-43
Number of pages21
DOIs
Publication statusPublished - 2017

Publication series

NameStudies in Fuzziness and Soft Computing
Volume356
ISSN (Print)1434-9922

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Mathematics

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