http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Type-2 Fuzzy Decision-Making Theories, Methodologies and Applications
XV, 271 p. 43 illus., 29 illus. in color. online resource.
This book integrates the type-2 fuzzy sets and multiple criteria decision making analysis in recent years and offers an authoritative treatise on the essential topics, both at the theoretical and applied end. In this book, some basic theory, type-2 fuzzy sets, methodology, algorithms, are introduced and then some compelling case studies in decision problems are covered in depth. The authors offer an authoritative treatise on the essential topics, both at the theoretical and applied end; In a systematic and logically organized way, the book exposes the reader to the essentials of the theory of type-2 fuzzy sets, methodology, algorithms, and their applications. Numerous techniques of decision making are carefully generalized by bringing the ideas of type-2 fuzzy sets; this concerns well-known methods including TOPSIS, Analytical Network Process, TODIM, and VIKOR. This book exposes the readers to the essentials of the theory of type-2 fuzzy sets, methodology, algorithms, and their applications.
Chapter 1 Type-2 Fuzzy Sets and Its Extensions -- Chapter 2 Multiple criteria decision making with type-2 fuzzy information -- Chapter 3 Interval type-2 fuzzy aggregation operations based on Maclaurin means and its extensions -- Chapter 4 Interval type-2 fuzzy combined ranking method -- Chapter 5 Interval type-2 fuzzy decision making based on TOPSIS -- Chapter 6 Interval type-2 fuzzy decision making based on ANP -- Chapter 7 Interval type-2 fuzzy decision making based on TODIM -- Chapter 8 Interval type-2 fuzzy decision making based on LINMAP -- Chapter 9 An integrated interval type-2 fuzzy decision making based on VIKOR and Prospect theory -- Chapter 10 Interval type-2 fuzzy decision making based on Granular Computing and its application in personalized recommendation -- Chapter 11 Interval Type-2 Fuzzy Group Decision Making by Integrating Improved Best Worst Method with COPRAS for Emergency Material Supplier Selection.