Overview
- Editors:
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Humberto Bustince
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Department of Automatics and Computation, Universidad Pública de Navarra, Spain
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Francisco Herrera
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Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada, Periodista Daniel Saucedo Aranda s/n, Spain
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Javier Montero
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Faculty of Mathematics, Universidad Complutense, 28040 Madrid, Spain
- Recent advances of fuzzy sets and their extensions
- Special focus on fuzzy logic foundations (representation and aggregation) and computer vision applications, decision making, web intelligence and data mining
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Table of contents (34 chapters)
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Foundations: Representation and Aggregation
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- Simon Coupland, Robert John
Pages 3-22
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- Eric C. C. Tsang, QingCai Chen, Suyun Zhao, Daniel S. Yeung, Xizhao Wang
Pages 45-64
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- Gleb Beliakov, Tomasa Calvo
Pages 99-120
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- Radko Mesiar, Anna Kolesárová, Tomasa Calvo, Magda Komorníková
Pages 121-144
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- Tomasa Calvo, Gleb Beliakov
Pages 145-162
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- Glad Deschrijver, Etienne Kerre
Pages 183-203
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From Decision Making to Data Mining, Web Intelligence and Computer Vision
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Front Matter
Pages 205-205
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- János Fodor, Bernard de Baets
Pages 207-217
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- Francisco Chiclana, Enrique Herrera-Viedma, Sergio Alonso, Ricardo Alberto, Marques Pereira
Pages 219-237
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- Salvatore Greco, Benedetto Matarazzo, Roman Słowiński
Pages 239-261
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- Janusz Kacprzyk, Sławomir Zadrożny, Mario Fedrizzi, Hannu Nurmi
Pages 263-295
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- Bonifacio Llamazares, José Luis García-Lapresta
Pages 297-315
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- Luis Martínez, Luis G. Pérez, Jun Liu
Pages 317-334
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- Eulalia Szmidt, Janusz Kacprzyk
Pages 335-355
About this book
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.
Editors and Affiliations
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Department of Automatics and Computation, Universidad Pública de Navarra, Spain
Humberto Bustince
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Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada, Periodista Daniel Saucedo Aranda s/n, Spain
Francisco Herrera
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Faculty of Mathematics, Universidad Complutense, 28040 Madrid, Spain
Javier Montero