Discrete Fuzzy Measures: Computational Aspects
暫譯: 離散模糊度量:計算方面
Beliakov, Gleb, James, Simon, Wu, Jian-Zhang
- 出版商: Springer
- 出版日期: 2019-06-04
- 售價: $5,230
- 貴賓價: 9.5 折 $4,969
- 語言: 英文
- 頁數: 260
- 裝訂: Quality Paper - also called trade paper
- ISBN: 303015307X
- ISBN-13: 9783030153076
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商品描述
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.
商品描述(中文翻譯)
本書針對從事多準則決策研究與實踐的計算機科學家、IT 專家、數學家、知識工程師和程式設計師。模糊度量(fuzzy measures),也稱為容量(capacities),允許將偏好程度、支持度或模糊隸屬度結合成一個代表性值,同時考慮輸入之間的相互作用。相互增強或冗餘的概念通過模糊度量的係數明確建模,而模糊積分(fuzzy integrals),如 Choquet 和 Sugeno 積分,則用於結合這些輸入。本書基於作者之前發表的專著,探討聚合的不同方面,特別專注於 Choquet 和 Sugeno 積分。它呈現了有關模糊度量計算、新的數據學習方法及建模相互作用的一些新發現。本書不需要深厚的數學背景,因為所有相關概念都有解釋。它旨在成為一部簡明、及時且自足的指南,幫助讀者在多準則決策領域中使用模糊度量。