Isbn: 9783790812565 - introduction to neuro-fuzzy systems (advances in soft computing) (advances in intelligent and soft computing, 2, band 2) (3 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Physica, 2000

    3790812560 / 9783790812565

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    Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,500grams, ISBN:9783790812565.

  • Sprache: Englisch

    Verlag: Physica, 1999

    3790812560 / 9783790812565

    • Softcover

    Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections

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    Zustand: New. In English.

  • Sprache: Englisch

    Verlag: Physica, 1999

    3790812560 / 9783790812565

    • Softcover

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    Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 304 | Sprache: Englisch | Produktart: Bücher | Fuzzy sets were introduced by Zadeh (1965) as a means of representing and manipulating data that was not precise, but rather fuzzy. Fuzzy logic pro­ vides an inference morphology that enables approximate human reasoning capabilities to be applied to knowledge-based systems. The theory of fuzzy logic provides a mathematical strength to capture the uncertainties associ­ ated with human cognitive processes, such as thinking and reasoning. The conventional approaches to knowledge representation lack the means for rep­ resentating the meaning of fuzzy concepts. As a consequence, the approaches based on first order logic and classical probablity theory do not provide an appropriate conceptual framework for dealing with the representation of com­ monsense knowledge, since such knowledge is by its nature both lexically imprecise and noncategorical. The developement of fuzzy logic was motivated in large measure by the need for a conceptual framework which can address the issue of uncertainty and lexical imprecision. Some of the essential characteristics of fuzzy logic relate to the following [242]. ¿ In fuzzy logic, exact reasoning is viewed as a limiting case of ap­ proximate reasoning. ¿ In fuzzy logic, everything is a matter of degree. ¿ In fuzzy logic, knowledge is interpreted a collection of elastic or, equivalently, fuzzy constraint on a collection of variables. ¿ Inference is viewed as a process of propagation of elastic con­ straints. ¿ Any logical system can be fuzzified. There are two main characteristics of fuzzy systems that give them better performance für specific applications.