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Uncertainty Data in Interval-Valued Fuzzy Set Theory: Properties, Algorithms and Applications: 367 (Studies in Fuzziness and Soft Computing) - Tapa blanda

Libro 134 de 183: Studies in Fuzziness and Soft Computing

Pękala, Barbara

 
9783030067434: Uncertainty Data in Interval-Valued Fuzzy Set Theory: Properties, Algorithms and Applications: 367 (Studies in Fuzziness and Soft Computing)
Tapa blanda
ISBN 10: 3030067432 ISBN 13: 9783030067434
Editorial: Springer, 2018

Sinopsis

This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov’s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.

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De la contraportada

This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data.

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Editorial
Springer
Año de publicación
2018
Idioma
Inglés
ISBN 10 
3030067432
ISBN 13 
9783030067434
Encuadernación
Tapa blanda
Número de páginas
196
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