Isbn: 9783642092909 - fuzzy sets and their extensions: representation, aggregation and models: intelligent systems from decision making to data mining, web intelligence and computer vision: 220 (9 risultati)

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      Taschenbuch. Condizione: Neu. Fuzzy Sets and Their Extensions: Representation, Aggregation and Models | Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision | Humberto Bustince (u. a.) | Taschenbuch | Studies in Fuzziness and Soft Computing | xx | Englisch | 2010 | Springer | EAN 9783642092909 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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      Editore: Springer, 2010

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      Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent advances of fuzzy sets and their extensionsSpecial focus on fuzzy logic foundations (representation and aggregation) and computer vision applications, decision making, web intelligence and data miningThis carefully edited book pr.

    • Lingua: Inglese

      Editore: Springer Berlin Heidelberg Nov 2010, 2010

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      Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This carefully edited book presents an up-to-date state of current research in the use of fuzzy sets and their extensions. It pays particular attention to foundation issues and to their application to four important areas where fuzzy sets are seen to be an important tool for modeling and solving problems. The book's 34 chapters deal with the subject with clarity and effectiveness. They include four review papers introducing some non-standard representations 696 pp. Englisch.

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      Editore: Springer, Springer Nov 2010, 2010

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      Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Fuzzy Sets and Their Extensions: Representation, Aggregation and Models Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision Fuzzy sets are now more than 40 years old, and have come of age. However, the development of fuzzy set theory at the theoretical level, and its successful appli- tions to science and technology have often run in isolation. Only a little part of the theoretical apparatus was effectively used in past applications. The most prominent ones, namely fuzzy rule-based modeling and control engineering, were directly - spired from a seminal paper by Lot Zadeh in 1973, suggesting how to use expert knowledge for synthetizing control laws, and from the rst experiments published by Abe Mamdani. Later in the eighties, when spectacular applications were bl- soming in Japan, fuzzy rule-based systems were systematized and simpli ed by Michio Sugeno and colleagues, and became a basic approach to non-linear system modeling and control, soon hybridized with neural networks in the nineties. Thus fuzzy systems signi cantly contributed to the raise of computational intelligence, and a lot of learning techniques for the construction of (supposedly interpretable) fuzzy models from data were developed under the ag of soft computing. Even if this area was quite successful, it is patent that the role, in the success of fuzzy logic, of new fuzzy set-related concepts developed quite at the same time in themathematicalnicheofthefuzzyset communitywaslimited.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 696 pp. Englisch.

    • Lingua: Inglese

      Editore: J.B. Metzler, 2010

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      Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Fuzzy Sets and Their Extensions: Representation, Aggregation and Models Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision Fuzzy sets are now more than 40 years old, and have come of age. However, the development of fuzzy set theory at the theoretical level, and its successful appli- tions to science and technology have often run in isolation. Only a little part of the theoretical apparatus was effectively used in past applications. The most prominent ones, namely fuzzy rule-based modeling and control engineering, were directly - spired from a seminal paper by Lot Zadeh in 1973, suggesting how to use expert knowledge for synthetizing control laws, and from the rst experiments published by Abe Mamdani. Later in the eighties, when spectacular applications were bl- soming in Japan, fuzzy rule-based systems were systematized and simpli ed by Michio Sugeno and colleagues, and became a basic approach to non-linear system modeling and control, soon hybridized with neural networks in the nineties. Thus fuzzy systems signi cantly contributed to the raise of computational intelligence, and a lot of learning techniques for the construction of (supposedly interpretable) fuzzy models from data were developed under the ag of soft computing. Even if this area was quite successful, it is patent that the role, in the success of fuzzy logic, of new fuzzy set-related concepts developed quite at the same time in themathematicalnicheofthefuzzyset communitywaslimited.