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As a new interpretable model, three-way decision has also received academic attention in machine learning. With respect to different hesitant fuzzy information, this book deeply discusses the deduction process of decision rules of three-way decision and generates interpretable knowledge with the risk semantics. It further explores the applications of three-way decision to support healthcare management. This book is used as a reference for engineers, technicians, and researchers who are working in the fields of management science, operation management, computer science, information management, fuzzy mathematics, business intelligence, and other fields. It also serves as a textbook for postgraduate and senior undergraduate students of the relevant professional institutions of higher learning.
This book gives a thorough and systematic introduction to the latest research results about fuzzy decision-making method based on prospect theory. It includes eight chapters: Introduction, Intuitionistic fuzzy MADM based on prospect theory, QUALIFLEX based on prospect theory with probabilistic linguistic information, Group PROMETHEE based on prospect theory with hesitant fuzzy linguistic information, Prospect consensus with probabilistic hesitant fuzzy preference information, Improved TODIM based on prospect theory and the improved TODIM with probabilistic hesitant fuzzy information, etc. This book is suitable for the researchers in the fields of fuzzy mathematics, operations research, behavioral science, management science and engineering, etc. It is also useful as a textbook for postgraduate and senior-year undergraduate students of the relevant professional institutions of higher learning.
The book introduces readers to some of the latest advances in and approaches to decision-making methods based on thermodynamic characters and hesitant fuzzy linguistic preference relations.
This book provides a comprehensive and systematic introduction to the latest research in the field, including measurement methods, consistency methods, group consensus and large-scale group consensus decision-making methods, as well as their practical applications.
This book introduces readers to the latest advances in and approaches to intuitionistic fuzzy decision-making methods. Examining a host of decision-making methods, most of which are based on intuitionistic fuzzy aggregation operators, its goal is to offer readers a new way to study decision-making methods in the intuitionistic fuzzy environment.
It reports on the authors' latest research, as well as on others' research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information.
After introducing the intuitionistic fuzzy numbers' operational laws and their geometrical and algebraic properties, the book defines the concept of intuitionistic fuzzy functions and presents the research on the derivative, differential, indefinite integral and definite integral of intuitionistic fuzzy functions.
This book presents a systematic introduction to hesitant fuzzy theory. Coverage includes hesitant fuzzy aggregation techniques, hesitant fuzzy measures, hesitant fuzzy clustering algorithms and hesitant fuzzy multi-attribute decision making methods.
This comprehensive introduction to methods of 'intuitionistic' decision-making explains in detail a variety of models and approaches to interactive decision-making with intuitionistic fuzzy information, as well as systematic coverage of aggregation techniques.
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