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Fuzzy Logic

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 63))

Abstract

This chapter introduces the basic concepts, notation, and basic operations for fuzzy sets that will be needed in the following chapters. Since research on Fuzzy Set Theory has been underway for over 30 years now, it is practically impossible to cover all aspects of current developments in this area. Therefore, the main goal of this chapter is to provide an introduction to and a summary of the basic concepts and operations that are relevant to the study of fuzzy sets. We also introduce in this chapter the definition of linguistic variables and linguistic values and explain how to use them in fuzzy rules, which are an efficient tool for quantitative modelling of words or sentences in a natural or artificial language. By interpreting fuzzy rules as fuzzy relations, we describe different schemes of fuzzy reasoning, where inference procedures based on the concept of the compositional rule of inference are used to derive conclusions from a set of fuzzy rules and known facts. Fuzzy rules and fuzzy reasoning are the basic components of fuzzy inference systems, which are the most important modelling tool, based on fuzzy set theory.

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© 2001 Physica-Verlag Heidelberg

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Castillo, O., Melin, P. (2001). Fuzzy Logic. In: Soft Computing for Control of Non-Linear Dynamical Systems. Studies in Fuzziness and Soft Computing, vol 63. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1832-1_2

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  • DOI: https://doi.org/10.1007/978-3-7908-1832-1_2

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-662-00367-1

  • Online ISBN: 978-3-7908-1832-1

  • eBook Packages: Springer Book Archive

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