Granularities-Driven Hesitant Fuzzy Linguistic Decision Making - Zheng, Yuanhang;Xu, Zeshui
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This book introduces a state-of-the-art extension of fuzzy sets that is hesitant fuzzy linguistic term sets with granularity levels, and based on the fuzzy technique, several granularities-driven hesitant fuzzy linguistic decision-making methods are introduced to provide powerful tools to solve actual problems. Motivated from the idea of granular computing, the technique of hesitant fuzzy linguistic term sets with granularity levels is constructed, which not only brings flexibility and individuality for the linguistic model, but also provides a possibility to process a large amount of…mehr

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Produktbeschreibung
This book introduces a state-of-the-art extension of fuzzy sets that is hesitant fuzzy linguistic term sets with granularity levels, and based on the fuzzy technique, several granularities-driven hesitant fuzzy linguistic decision-making methods are introduced to provide powerful tools to solve actual problems. Motivated from the idea of granular computing, the technique of hesitant fuzzy linguistic term sets with granularity levels is constructed, which not only brings flexibility and individuality for the linguistic model, but also provides a possibility to process a large amount of linguistic information in group decision-making efficiently and accurately. Thus, the researches on granularities-driven hesitant fuzzy linguistic decision making, can provide an effective way to solve practical decision-making problems based on complex linguistic information, and enrich the research system of decision-making and granular computing in theory and practice.

In specific, this book introduces the construction of hesitant fuzzy linguistic term sets with granularity levels, and methods of handling attribute dependence, attribute reduction, single-objective group decision-making, and bi-objective group decision-making. The above decision-making methods are applied to the evaluation of medical and health management, and the effectiveness and advantages of the methods are verified by simulation comparison and analysis. Therefore, this book has not only important theoretical significance, but also broad application prospects.
Autorenporträt
Yuanhang Zheng received the Ph.D. degree in management science and engineering from Sichuan University, China, in 2022, and received the B.S. degree from Sichuan University, China, in 2017. She is currently an Associate researcher with the College of Computer, Sichuan University. She has been elected as the IEEE Senior Member. As the first author, she has published 1 monographs by Springer. As the first/corresponding author, she has published more than 10 high-level research papers in IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Fuzzy Systems, Expert Systems with Applications, Knowledge-Based Systems, Applied Soft Computing, International Journal of Intelligent Systems, Artificial Intelligence Review, etc. Those papers have gained more than 270 citations in Google Scholar and her corresponding h-index is 8. Now she has hosted the National Natural Science Foundation of China and Natural Science Foundation of Sichuan Province. Her current research interests include intelligent decision-making, large-scale group decision making and intelligent medical management. Dr. Zheng has a motto: All experience is wealth. 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 a Postdoctoral Researcher with School of Economics and Management, Tsinghua University, China. He was a Distinguished Young Scholar of the National Natural Science Foundation of China and the Chang Jiang Scholar of the Ministry of Education of China. He is currently a Chair Professor with Sichuan University, Chengdu. He has been elected as the member of Academia Europaea, European Academy of Sciences and Arts, European Academy of Natural Sciences, and International Academy for Systems and Cybernetic Sciences, the Distinguished Fellow of IETI, the Fellow of IEEE, IFSA, RSA, IET, ORS, BCS, IAAM, AAIA, VEBLEO, AIIA, and ACIS. He is ranked 30th in 2019 single year scientific impact and 162th 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 21 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 90,000 citations in Google Scholar, his h-index is 148. He is currently the 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.