Uncertainty Data in Interval-Valued Fuzzy Set Theory : Properties, Algorithms and Applications / by Barbara Pękala.
By: Pe̜kala, Barbara, autor
Contributor(s): SpringerLink (Online service)
Series: (Studies in Fuzziness and Soft Computing, 1434-9922; 367); (Intelligent Technologies and Robotics (Springer-42732)).Publisher: Cham : Imprint: Springer, 2019Description: 1 recurso en línea (XIV, 181 páginas).ISBN: 9783319939100.Subject: Conjuntos difusos
| Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA248.5 2019 EB (Browse shelf(Opens below)) | Acceso electrónico | eBooks26062272 |
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| QA248.5 2019 EB Backward fuzzy rule interpolation | QA248.5 2019 EB Dealing with imbalanced and weakly labelled data in machine learning using fuzzy and rough set methods | QA248.5 2019 EB An introduction to analytical fuzzy plane geometry | QA248.5 2019 EB Uncertainty Data in Interval-Valued Fuzzy Set Theory : Properties, Algorithms and Applications | QA248.5 2019 EB Fuzzy Linear Programming : Solution Techniques and Applications | QA248.5 2019 EB Fuzzy Sets and Operations Research | QA248.5 2020 EB Interval-valued intuitionistic fuzzy sets |
Introduction to Fuzzy Sets -- Interval-Valued Fuzzy Relations -- Applications -- Summary and Open Problem.
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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