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Discrete fuzzy measures = computatio...

Beliakov, Gleb.

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Discrete fuzzy measures = computational aspects /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Discrete fuzzy measures/ by Gleb Beliakov, Simon James, Jian-Zhang Wu.
其他題名:	computational aspects /
作者:	Beliakov, Gleb.
其他作者:	James, Simon.
出版者:	Cham :Springer International Publishing : : 2020.,
面頁冊數:	xiv, 245 p. :ill. (some col.), digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Fuzzy measure theory. -
電子資源:	https://doi.org/10.1007/978-3-030-15305-2
ISBN:	9783030153052

Discrete fuzzy measures = computational aspects /
Beliakov, Gleb.

Discrete fuzzy measurescomputational aspects /[electronic resource] :by Gleb Beliakov, Simon James, Jian-Zhang Wu. - Cham :Springer International Publishing :2020. - xiv, 245 p. :ill. (some col.), digital ;24 cm. - Studies in fuzziness and soft computing,v.3821434-9922 ;. - Studies in fuzziness and soft computing ;v.382..

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.

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.

ISBN: 9783030153052

Standard No.: 10.1007/978-3-030-15305-2doiSubjects--Topical Terms:

2055896
Fuzzy measure theory.

LC Class. No.: QA312.5

Dewey Class. No.: 515.42

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520 $a 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.
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