Fuzzy Set Theory—and Its ApplicationsSince its inception, the theory of fuzzy sets has advanced in a variety of ways and in many disciplines. Applications of fuzzy technology can be found in artificial intelligence, computer science, control engineering, decision theory, expert systems, logic, management science, operations research, robotics, and others. Theoretical advances have been made in many directions. The primary goal of Fuzzy Set Theory - and its Applications, Fourth Edition is to provide a textbook for courses in fuzzy set theory, and a book that can be used as an introduction. To balance the character of a textbook with the dynamic nature of this research, many useful references have been added to develop a deeper understanding for the interested reader. Fuzzy Set Theory - and its Applications, Fourth Edition updates the research agenda with chapters on possibility theory, fuzzy logic and approximate reasoning, expert systems, fuzzy control, fuzzy data analysis, decision making and fuzzy set models in operations research. Chapters have been updated and extended exercises are included. |
From inside the book
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Page xvi
... thanked for contributing so much over the past decade to the advancement of the theory of fuzzy sets as a scientist , educator , administrator , and organizer . L.A. Zadeh Since its inception 20 years ago , the theory of xvi FOREWORD.
... thanked for contributing so much over the past decade to the advancement of the theory of fuzzy sets as a scientist , educator , administrator , and organizer . L.A. Zadeh Since its inception 20 years ago , the theory of xvi FOREWORD.
Page 3
... Zadeh referred to the second point when he wrote , " As the complexity of a system increases , our ability to make precise and yet significant statements about its behaviour diminishes until a threshold is reached beyond which preci ...
... Zadeh referred to the second point when he wrote , " As the complexity of a system increases , our ability to make precise and yet significant statements about its behaviour diminishes until a threshold is reached beyond which preci ...
Page 5
... Zadeh [ 1965 ] and Goguen [ 1967 , 1969 ] show the intention of the authors to generalize the classical notion of a set and a proposition [ statement ] to accommodate fuzziness in the sense described in section 1.1 . Zadeh [ 1965 , p ...
... Zadeh [ 1965 ] and Goguen [ 1967 , 1969 ] show the intention of the authors to generalize the classical notion of a set and a proposition [ statement ] to accommodate fuzziness in the sense described in section 1.1 . Zadeh [ 1965 , p ...
Page 8
... Zadeh expressed his intention to have fuzzy set theory considered as a tool to determine approximate solutions of real problems in an efficient or affordable way . This goal has never really been achieved successfully . In the recent ...
... Zadeh expressed his intention to have fuzzy set theory considered as a tool to determine approximate solutions of real problems in an efficient or affordable way . This goal has never really been achieved successfully . In the recent ...
Page 15
... fuzzy set . One final feature of a fuzzy set , which we will use frequently in later chap- ters , is its cardinality or " power " [ Zadeh 1981c ] . Definition 2-5 For a finite fuzzy set Ć , the FUZZY SETS - BASIC DEFINITIONS 15.
... fuzzy set . One final feature of a fuzzy set , which we will use frequently in later chap- ters , is its cardinality or " power " [ Zadeh 1981c ] . Definition 2-5 For a finite fuzzy set Ć , the FUZZY SETS - BASIC DEFINITIONS 15.
Contents
1 | |
8 | |
22 | |
4 | 44 |
The Extension Principle and Applications | 54 |
Fuzzy Relations on Sets and Fuzzy Sets | 71 |
3 | 82 |
7 | 88 |
Applications of Fuzzy Set Theory | 139 |
3 | 154 |
4 | 160 |
5 | 169 |
Fuzzy Sets and Expert Systems | 185 |
Fuzzy Control | 223 |
Fuzzy Data Bases and Queries | 265 |
Decision Making in Fuzzy Environments | 329 |
3 | 95 |
4 | 105 |
2 | 122 |
4 | 131 |
Applications of Fuzzy Sets in Engineering and Management | 371 |
Empirical Research in Fuzzy Set Theory | 443 |
Future Perspectives | 477 |
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Common terms and phrases
a-level aggregation algebraic algorithm applications of fuzzy approach approximately areas base basic Bezdek chapter classical computational concepts considered constraints crisp criteria customers data analysis DataEngine decision defined definition defuzzification degree of membership described determine domain Dubois and Prade elements engineering example expert systems feature formal Fril fuzzy c-means fuzzy clustering fuzzy control fuzzy control systems fuzzy function fuzzy graph fuzzy logic fuzzy measures fuzzy numbers fuzzy relation fuzzy set Ć fuzzy set theory goal inference inference engine input integral intersection interval linear programming linguistic variable Mamdani mathematical measure of fuzziness membership function methods min-operator objective function operators optimal parameters possibility distribution probability probability theory problem properties respect rules scale level scheduling semantic solution structure Sugeno t-conorms t-norms Table tion trajectories truth tables truth values uncertainty vector x₁ Yager Zadeh Zimmermann µĆ(x µµ(x