Hesitant Fuzzy and Probabilistic Information Fusion

Theory and Applications
2024
ISBN: 978-981-97-3139-8
Verlag: Springer Nature Singapore

Buch, Englisch, 145 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 412 g

Reihe: Uncertainty and Operations Research

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.

Zielgruppe

Research

Autoren/Hrsg.

Su, Zhan

Zhang, Shen

Xu, Zeshui

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Entscheidungstheorie, Sozialwahltheorie
• Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
• Wirtschaftswissenschaften Betriebswirtschaft Management Entscheidungsfindung

Inhaltsverzeichnis

Introduction.- Probability-based hesitant fuzzy opinion dynamics decision-making method.- Distribution-based decision-making method for dual hesitant fuzzy information.- Multi-attribute decision-making method based on probabilistic hesitant fuzzy entropy.- Probability-based integration for continuous hesitant fuzzy information in group decision-making.- Probability-based political risk assessment in the Belt and Road investment.- Appendix I.- Appendix II.

Über Autor(innen)

Zhan Su received the Ph.D. degree in computer science and technology from Army Engineering University of PLA, Nanjing, China, in 2021. She is currently Associated Professor with School of Digital Arts, Nanjing Vocational College of Information Technology, Nanjing, China. She has contributed 20 journal articles to professional journals, and her current research interests include fuzzy sets, decision-making, and information fusion.

Zeshui Xu received the Ph.D. degree in management science and engineering from Southeast University, Nanjing, China, in 2003. From October 2005 to December 2007, he was Postdoctoral Researcher with School of Economics and Management, Tsinghua University, China. He was Distinguished Young Scholar of the National Natural Science Foundation of China and Chang Jiang Scholar of the Ministry of Education of China. He is currently Chair Professor with Sichuan University, Chengdu. He has been elected as Member of Academia Europaea, European Academy of Sciences and Arts, European Academy of Natural Sciences, and International Academy for Systems and Cybernetic Sciences; Distinguished Fellow of IETI; and Fellow of IEEE, IFSA, RSA, IET, ORS, BCS, IAAM, AAIA, VEBLEO, and AIIA. He is ranked 30th in 2019 single-year scientific impact and 162nd in career scientific impact among World’s top 100,000 Scientists and ranked 40th among the World’s best scientists in the arena of Computer Science in 2023. He has published 19 monographs by Springer and contributed more than 900 SCI/SSCI articles to professional journals. He is among the world’s top 1% most highly cited researchers with more than 89,000 citations in Google Scholar, and his h-index is 147. He is currently Associate Editor of IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, Information Sciences, Artificial Intelligence Review, Cognitive Computation, Applied Intelligence, Journal of the Operational Research, Fuzzy Optimization and Decision Making, etc. His current research interests include decision-making theory and methodology, optimization algorithms, information fusion, and big data analytics.

Shen Zhang received the Ph.D. degree in management science from Business School, Sichuan University, Chengdu, China, in 2021. He has contributed 7 journal articles to professional journals, and his current research interests include decision-making and fuzzy sets.