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
Results 1-5 of 53
Page xv
... important issue in the theory of fuzzy sets that does not have a counterpart in the theory of crisp sets relates to the combination of fuzzy sets through disjunc- tion and conjunction or , equivalently , union and intersection ...
... important issue in the theory of fuzzy sets that does not have a counterpart in the theory of crisp sets relates to the combination of fuzzy sets through disjunc- tion and conjunction or , equivalently , union and intersection ...
Page xvi
... important role in the representa- tion of meaning , in the management of uncertainty in expert systems , and in appli- cations of the theory of fuzzy sets to decision analysis . As one of the leading contributors to and practitioners of ...
... important role in the representa- tion of meaning , in the management of uncertainty in expert systems , and in appli- cations of the theory of fuzzy sets to decision analysis . As one of the leading contributors to and practitioners of ...
Page xxiii
... important . The applicational relevance of these research results , however , is often not obvious and only perceivable by very advanced and specialized theoreticians . New developments in fuzzy technology follow more Preface to the ...
... important . The applicational relevance of these research results , however , is often not obvious and only perceivable by very advanced and specialized theoreticians . New developments in fuzzy technology follow more Preface to the ...
Page xxv
... importance in practice . In chapter 11 primarily a section for defuzzification has been added for the same reason . Chapter 12 has been added because the application of fuzzy technology in information processing is already important and ...
... importance in practice . In chapter 11 primarily a section for defuzzification has been added for the same reason . Chapter 12 has been added because the application of fuzzy technology in information processing is already important and ...
Page 2
... important in the formal sciences : ( a ) The relationship between the language and the domain must be closer because they are in a sense produced through and for each other ; ( b ) extensions of formalisms and models must necessarily be ...
... important in the formal sciences : ( a ) The relationship between the language and the domain must be closer because they are in a sense produced through and for each other ; ( b ) extensions of formalisms and models must necessarily be ...
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 à 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 µÃ(x µµ(x