Uncertainty data in interval-valued fuzzy set theory [electronic resource] : properties, algorithms and applications / by Barbara Pekala.
- 作者: Pekala, Barbara.
- 其他作者:
- 其他題名:
- Studies in fuzziness and soft computing ;
- 出版: Cham : Springer International Publishing :Imprint: Springer 2019.
- 叢書名: Studies in fuzziness and soft computing,v.367
- 主題: Fuzzy sets. , Uncertainty (Information theory) , Computational Intelligence. , Operations Research, Management Science. , Artificial Intelligence. , Operations Research/Decision Theory.
- ISBN: 9783319939100 (electronic bk.) 、 9783319939094 (paper)
- URL:
點擊此處查看電子書
電子書(校內)
- 一般註:Introduction to Fuzzy Sets -- Interval-Valued Fuzzy Relations -- Applications -- Summary and Open Problem. E1084學校採購電子書
-
讀者標籤:
- 系統號: 000275348 | 機讀編目格式
館藏資訊

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.
摘要註
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.




