Discrete Fuzzy Measures: Computational Aspects: Studies in Fuzziness and Soft Computing, cartea 382
Autor Gleb Beliakov, Simon James, Jian-Zhang Wuen Limba Engleză Hardback – 27 mar 2019
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Specificații
ISBN-13: 9783030153045
ISBN-10: 3030153045
Pagini: 246
Ilustrații: XIV, 245 p. 44 illus., 38 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.54 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Fuzziness and Soft Computing
Locul publicării:Cham, Switzerland
ISBN-10: 3030153045
Pagini: 246
Ilustrații: XIV, 245 p. 44 illus., 38 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.54 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Fuzziness and Soft Computing
Locul publicării:Cham, Switzerland
Cuprins
Introduction.- Types of Fuzzy Measures.- Value and Interaction Indices.- Representations.- Fuzzy Integrals.- Symmetric Fuzzy Measures: OWA.- k–order Fuzzy Measures and k–order Aggregation Functions.- Learning Fuzzy Measures.- Index.
Textul de pe ultima copertă
This book addresses computer scientists, IT specialists, mathematicians, knowledge engineers and programmers, who are engaged in research and practice of multicriteria decision making. Fuzzy measures, also known as capacities, allow one to combine degrees of preferences, support or fuzzy memberships into one representative value, taking into account interactions between the inputs. The notions of mutual reinforcement or redundancy are modeled explicitly through coefficients of fuzzy measures, and fuzzy integrals, such as the Choquet and Sugeno integrals combine the inputs. Building on previous monographs published by the authors and dealing with different aspects of aggregation, this book especially focuses on the Choquet and Sugeno integrals. It presents a number of new findings concerning computation of fuzzy measures, learning them from data and modeling interactions. The book does not require substantial mathematical background, as all the relevant notions are explained. It is intended as concise, timely and self-contained guide to the use of fuzzy measures in the field of multicriteria decision making.
Caracteristici
Presents new findings concerning aggregation of inputs Offers new insights into computational aspects of fuzzy measures Explains all the necessary mathematical concepts