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Probabilistic linguistic two-sided matching decision-making methods and applications

Record Type:	Electronic resources : Monograph/item
Title/Author:	Probabilistic linguistic two-sided matching decision-making methods and applications/ by Bo Li, Zeshui Xu.
Author:	Li, Bo.
other author:	Xu, Zeshui.
Published:	Cham :Springer Nature Switzerland : : 2025.,
Description:	xi, 111 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	1 Introductio -- 2. Literature review -- 3. Probabilistic linguistic static two-sided matching method based on pairwise compared preference relationship -- 4. Multi-stage probabilistic linguistic matching method based on improved preference relationship consistency algorithm -- 5. Probabilistic linguistic two-sided matching with attribute weights complete unknown.
Contained By:	Springer Nature eBook
Subject:	Decision making - Mathematical models. -
Online resource:	https://doi.org/10.1007/978-3-031-88562-4
ISBN:	9783031885624

Probabilistic linguistic two-sided matching decision-making methods and applications
Li, Bo.

Probabilistic linguistic two-sided matching decision-making methods and applications[electronic resource] /by Bo Li, Zeshui Xu. - Cham :Springer Nature Switzerland :2025. - xi, 111 p. :ill. (chiefly color), digital ;24 cm. - Studies in fuzziness and soft computing,v. 4361860-0808 ;. - Studies in fuzziness and soft computing ;v. 436..

1 Introductio -- 2. Literature review -- 3. Probabilistic linguistic static two-sided matching method based on pairwise compared preference relationship -- 4. Multi-stage probabilistic linguistic matching method based on improved preference relationship consistency algorithm -- 5. Probabilistic linguistic two-sided matching with attribute weights complete unknown.

This book tackles the intricacies of decision-making processes where alternatives stem from distinct, finite sets. Discover the cutting-edge in decision-making with our groundbreaking book on complex two-sided matching methods. Harnessing the power of probabilistic linguistic term sets, it introduces innovative methods that enhance matching efficiency and practicality. It addresses the pressing question of how to navigate and optimize in scenarios with multifaceted matching challenges, offering an exploration into the psychological perceptions of agents through consistency checks and pairwise comparisons. It delves into the unknowns of static matching with multiple attribute weights, extends its scope to multi-sided agent sets in complex matching, and introduces dynamic screening mechanisms to refine the matching process. This book is not just a theoretical exploration. It lays the groundwork for intelligent matching algorithms and group mechanisms, providing actionable insights for technical supply and demand allocation, emergency personnel dispatch, and multi-stage medical management scheme selection. The effectiveness of these methods is backed by comparative analyses and simulation experiments, proving their superiority in real-world applications. Embrace the future of decision-making with our book, a must-read for those seeking to master complex matching scenarios and unlock practical solutions.

ISBN: 9783031885624

Standard No.: 10.1007/978-3-031-88562-4doiSubjects--Topical Terms:

565918
Decision making
--Mathematical models.

LC Class. No.: QA279.4

Dewey Class. No.: 519.542

Probabilistic linguistic two-sided matching decision-making methods and applications
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505 0 $a 1 Introductio -- 2. Literature review -- 3. Probabilistic linguistic static two-sided matching method based on pairwise compared preference relationship -- 4. Multi-stage probabilistic linguistic matching method based on improved preference relationship consistency algorithm -- 5. Probabilistic linguistic two-sided matching with attribute weights complete unknown.
520 $a This book tackles the intricacies of decision-making processes where alternatives stem from distinct, finite sets. Discover the cutting-edge in decision-making with our groundbreaking book on complex two-sided matching methods. Harnessing the power of probabilistic linguistic term sets, it introduces innovative methods that enhance matching efficiency and practicality. It addresses the pressing question of how to navigate and optimize in scenarios with multifaceted matching challenges, offering an exploration into the psychological perceptions of agents through consistency checks and pairwise comparisons. It delves into the unknowns of static matching with multiple attribute weights, extends its scope to multi-sided agent sets in complex matching, and introduces dynamic screening mechanisms to refine the matching process. This book is not just a theoretical exploration. It lays the groundwork for intelligent matching algorithms and group mechanisms, providing actionable insights for technical supply and demand allocation, emergency personnel dispatch, and multi-stage medical management scheme selection. The effectiveness of these methods is backed by comparative analyses and simulation experiments, proving their superiority in real-world applications. Embrace the future of decision-making with our book, a must-read for those seeking to master complex matching scenarios and unlock practical solutions.
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