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Sinopsis
This book introduces readers to the latest advances in and approaches to intuitionistic fuzzy decision-making methods. To do so, it explores a range of applications to practical decision-making problems, together with representative case studies. 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. Chiefly intended for practitioners and researchers working in the areas of risk management, decision-making under uncertainty, and operational research, the book can also be used as supplementary material for graduate and senior undergraduate courses in these areas.
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Acerca del autor
Zhinan Hao received the Ph.D. degree in computer science and technology from Army Engineering University of PLA, Nanjing, China, in 2018. He has contributed 4 journal articles to professional journals, and his current research interests include decision making and fuzzy sets.
Zeshui Xu received the Ph.D. degree in management science and engineering from Southeast University, Nanjing, China, in 2003. He is a Distinguished Young Scholar of the National Natural Science Foundation of China and the Chang Jiang Scholars of the Ministry of Education of China. He is currently a Professor with Business School, Sichuan University, Chengdu, China. He has contributed more than 450 journal articles to professional journals, and his current research interests include information fusion, decision making, and fuzzy sets.
Hua Zhao received the Ph.D. degree in military operation research from PLA University of Science and Technology, Nanjing, China, in 2011. She is currently an Associated Professor with Department of General Education, Army Engineering University of PLA, Nanjing, China. She has contributed more than 30 journal articles to professional journals, and her current research interests include clustering analysis, decision making and fuzzy sets.
De la contraportada
This book introduces readers to the latest advances in and approaches to intuitionistic fuzzy decision-making methods. To do so, it explores a range of applications to practical decision-making problems, together with representative case studies. 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. Chiefly intended for practitioners and researchers working in the areas of risk management, decision-making under uncertainty, and operational research, the book can also be used as supplementary material for graduate and senior undergraduate courses in these areas.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces a new intuitionistic fuzzy decision-making method based on a new distance measure and similarity measure for the intuitionistic fuzzy set Presents two types of intuitionistic fuzzy dynamic decision-making . Nº de ref. del artículo: 446298188
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Several Intuitionistic Fuzzy Multi-Attribute Decision Making Methods and Their Applications (Uncertainty and Operations Research)
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Several Intuitionistic Fuzzy Multi-Attribute Decision Making Methods and Their Applications
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book introduces readers to the latest advances in and approaches to intuitionistic fuzzy decision-making methods. To do so, it explores a range of applications to practical decision-making problems, together with representative case studies. 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. Chiefly intended for practitioners and researchers working in the areas of risk management, decision-making under uncertainty, and operational research, the book can also be used as supplementary material for graduate and senior undergraduate courses in these areas. 132 pp. Englisch. Nº de ref. del artículo: 9789811538933
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Several Intuitionistic Fuzzy Multi-Attribute Decision Making Methods and Their Applications
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces readers to the latest advances in and approaches to intuitionistic fuzzy decision-making methods. To do so, it explores a range of applications to practical decision-making problems, together with representative case studies. 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. Chiefly intended for practitioners and researchers working in the areas of risk management, decision-making under uncertainty, and operational research, the book can also be used as supplementary material for graduate and senior undergraduate courses in these areas. Nº de ref. del artículo: 9789811538933
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ISBN 10: 981153893X
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Taschenbuch. Condición: Neu. Neuware -This book introduces readers to the latest advances in and approaches to intuitionistic fuzzy decision-making methods. To do so, it explores a range of applications to practical decision-making problems, together with representative case studies. 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. Chiefly intended for practitioners and researchers working in the areas of risk management, decision-making under uncertainty, and operational research, the book can also be used as supplementary material for graduate and senior undergraduate courses in these areas.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 132 pp. Englisch. Nº de ref. del artículo: 9789811538933
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