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 xviii
Hans-Jürgen Zimmermann. volumes . The first volume contains the basic theory of fuzzy sets and some areas of ... set theory . Examples and exercises serve to illustrate the concepts even more clearly . For the interested or more advanced ...
Hans-Jürgen Zimmermann. volumes . The first volume contains the basic theory of fuzzy sets and some areas of ... set theory . Examples and exercises serve to illustrate the concepts even more clearly . For the interested or more advanced ...
Page xx
... fuzzy set theory only where and to the extent that it is needed , this book tries to offer a didactically prepared text which requires hardly any special math- ematical background of the reader . It tries to introduce fuzzy set theory ...
... fuzzy set theory only where and to the extent that it is needed , this book tries to offer a didactically prepared text which requires hardly any special math- ematical background of the reader . It tries to introduce fuzzy set theory ...
Page xxiii
... fuzzy set theory has its strength in modeling , interfacing humans with computers and modeling certain uncertainties . Particularly between fuzzy set theory and neural nets the synergies have been used to develop hybrid models and ...
... fuzzy set theory has its strength in modeling , interfacing humans with computers and modeling certain uncertainties . Particularly between fuzzy set theory and neural nets the synergies have been used to develop hybrid models and ...
Page xxv
... theoretical as well as application- oriented developments have become much more diversified and clear lead - times between theoretical ... FUZZY SETS 1.1 Crispness , Vagueness , PREFACE TO THE FOURTH EDITION XXV.
... theoretical as well as application- oriented developments have become much more diversified and clear lead - times between theoretical ... FUZZY SETS 1.1 Crispness , Vagueness , PREFACE TO THE FOURTH EDITION XXV.
Page 2
... set - theoretic sense ) of our thinking and feeling is much higher than the power of a living language . If in turn we compare the power of a living lan- guage with the ... FUZZY SET THEORY - AND ITS APPLICATIONS Fuzzy Set Theory ix 112.
... set - theoretic sense ) of our thinking and feeling is much higher than the power of a living language . If in turn we compare the power of a living lan- guage with the ... FUZZY SET THEORY - AND ITS APPLICATIONS Fuzzy Set Theory ix 112.
Contents
1 | |
8 | |
Extensions | 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