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Titlebook: Large-Scale Group Decision-Making with Uncertain and Behavioral Considerations; Methods and Applicat Tong Wu,Xinwang Liu Book 2023 The Edit

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樓主
發(fā)表于 2025-3-21 17:49:39 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Large-Scale Group Decision-Making with Uncertain and Behavioral Considerations
副標題Methods and Applicat
編輯Tong Wu,Xinwang Liu
視頻videohttp://file.papertrans.cn/582/581390/581390.mp4
概述Combines managerial, computerized, psychological, and sociological expertise from an interdisciplinary standpoint.Introduces several credible and efficient clustering analysis algorithms under uncerta
叢書名稱Uncertainty and Operations Research
圖書封面Titlebook: Large-Scale Group Decision-Making with Uncertain and Behavioral Considerations; Methods and Applicat Tong Wu,Xinwang Liu Book 2023 The Edit
描述This book investigates in detail large-scale group decision-making (LSGDM) problem, which has gradually evolved from the traditional group decision-making problem and has attracted more and more attention in the age of big data. Pursuing a holistic approach, the book establishes a fundamental framework for LSGDM with uncertain and behavioral considerations. To address the behavioral uncertainty and complexity of large groups of decision-makers, this book mainly focuses on new solutions of LSGDM problems using the interval type-2 fuzzy uncertainty theory and social network analysis techniques, including the exploration of uncertain clustering analysis, the consideration of social relationships, especially trust relationships, the construction of consensus evolution networks, etc. The book is intended for researchers and postgraduates who are interested in complex group decision-making in the new media era. Authors also investigate the similar features between LSGDM problems and group recommendations to study the applications of LSGDM methods. After reading this book, readers will have a new understanding of the LSGDM study under the real complicated context..?.
出版日期Book 2023
關鍵詞Large-scale Group Decision-making; Interval Type-2 Fuzzy Sets; Clustering Analysis; Community Detection
版次1
doihttps://doi.org/10.1007/978-981-19-8167-8
isbn_softcover978-981-19-8169-2
isbn_ebook978-981-19-8167-8Series ISSN 2195-996X Series E-ISSN 2195-9978
issn_series 2195-996X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 23:13:30 | 只看該作者
Large-Scale Group Decision-Making with Uncertain and Behavioral Considerations978-981-19-8167-8Series ISSN 2195-996X Series E-ISSN 2195-9978
板凳
發(fā)表于 2025-3-22 04:05:17 | 只看該作者
https://doi.org/10.1007/978-981-19-8167-8Large-scale Group Decision-making; Interval Type-2 Fuzzy Sets; Clustering Analysis; Community Detection
地板
發(fā)表于 2025-3-22 05:00:02 | 只看該作者
5#
發(fā)表于 2025-3-22 09:53:53 | 只看該作者
Large-Scale Group Decision-Making with Interval Type-2 Fuzzy Preferences,tion.?This chapter?introduces the interval type-2 fuzzy LSGDM?methods from the perspective of large-scale DMs and attributes, and introduces?a dynamic programming algorithm-based clustering model with IT2 FSs for LSGDM problems.
6#
發(fā)表于 2025-3-22 13:33:12 | 只看該作者
7#
發(fā)表于 2025-3-22 17:30:30 | 只看該作者
New Perspectives on Consensus Reaching Process in Large-Scale Group Decision-Making,onship, that is, the CRP and?clustering analysis should be an iterative process, and the CRP?may in turn cause changes in clustering results. This chapter?study the CRP in?LSGDM from the new perspectives of dynamic clustering and opinions adjustment costs.
8#
發(fā)表于 2025-3-22 22:05:52 | 只看該作者
9#
發(fā)表于 2025-3-23 02:02:58 | 只看該作者
Uncertain Theory and Group Decision-Making,This book mainly focuses on the uncertainty and decision-making behavior in LSGDM.?This chapter mainly introduces the preliminary knowledge related to uncertain LSGDM, including type-2 fuzzy set theory, GDM?theory and methods, and social relationship analysis techniques.
10#
發(fā)表于 2025-3-23 09:37:24 | 只看該作者
Interval Type-2 Fuzzy Large-Scale Group Decision-Making Considering Social Relationships,The popularity of social media brings familiar people closer and strangers together.?Social relationships not only provide new ideas for LSGDM?research, but also provide?new tools for dimension reduction of LSGDM. This chapter mainly discusses interval type-2 fuzzy?LSGDM?methods considering social relationships.
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