Hesitant fuzzy and probabilistic information fusion: theory and applications

By:

Su, Zhan

Contributor(s):

Material type: Text

TextSeries: Uncertainty and Operations ResearchPublication details: Springer Singapore 2024Description: xiv, 145 pISBN:

9789819731398

Subject(s):

Fuzzy decision making

DDC classification:

518 SU

Summary: This book introduces the current research progress on hesitant fuzzy decision-making based on probability theory and methods. From the perspectives of theory expansion, information fusion, and information mining, it explores novel perspectives, ideas, and techniques for addressing hesitant fuzzy uncertain decision-making problems and demonstrates them through practical applications and case studies. It aims to provide a reference for researchers, practitioners, and graduate students in the fields of decision analysis, fuzzy theory, and information fusion. (https://link.springer.com/book/10.1007/978-981-97-3140-4)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Operations Management & Quantitative Techniques	518 SU (Browse shelf(Opens below))	1	Available		007249

Table of content:
Introduction
Zhan Su, Zeshui Xu, Shen Zhang
Pages 1-15
Probability-Based Hesitant Fuzzy Opinion Dynamics Decision-Making Method
Zhan Su, Zeshui Xu, Shen Zhang
Pages 17-47
Distribution-Based Decision-Making Method for Dual Hesitant Fuzzy Information
Zhan Su, Zeshui Xu, Shen Zhang
Pages 49-72
Multi-Attribute Decision-Making Method Based on Probabilistic Hesitant Fuzzy Entropy
Zhan Su, Zeshui Xu, Shen Zhang
Pages 73-98
Probability-Based Integration for Continuous Hesitant Fuzzy Information in Group Decision-Making
Zhan Su, Zeshui Xu, Shen Zhang
Pages 99-125
Probability-Based Political Risk Assessment in the Belt and Road Investment
Zhan Su, Zeshui Xu, Shen Zhang
Pages 127-140
Back Matter
Pages 141-145

[https://link.springer.com/book/10.1007/978-981-97-3140-4]

This book introduces the current research progress on hesitant fuzzy decision-making based on probability theory and methods. From the perspectives of theory expansion, information fusion, and information mining, it explores novel perspectives, ideas, and techniques for addressing hesitant fuzzy uncertain decision-making problems and demonstrates them through practical applications and case studies. It aims to provide a reference for researchers, practitioners, and graduate students in the fields of decision analysis, fuzzy theory, and information fusion.

(https://link.springer.com/book/10.1007/978-981-97-3140-4)

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