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 76
Page ix
... Figure 9-2 Linguistic variable “ Probability ” . 144 Figure 9-3 Linguistic variable " Truth " . 145 Figure 9-4 Terms " True " and " False " . 146 Figure 10-1 Structure of an expert system . 189 Figure List of Figures 1 2 List of Figures 6 1 ...
... Figure 9-2 Linguistic variable “ Probability ” . 144 Figure 9-3 Linguistic variable " Truth " . 145 Figure 9-4 Terms " True " and " False " . 146 Figure 10-1 Structure of an expert system . 189 Figure List of Figures 1 2 List of Figures 6 1 ...
Page x
... Figure 10-2 Semantic net . 191 Figure 10-3 Linguistic descriptors . 205 Figure 10-4 Label sets for semantic representation . 205 Figure 10-5 Linguistic variables for occurrence and ... Figure 13-6 Dendogram for X LIST OF FIGURES.
... Figure 10-2 Semantic net . 191 Figure 10-3 Linguistic descriptors . 205 Figure 10-4 Label sets for semantic representation . 205 Figure 10-5 Linguistic variables for occurrence and ... Figure 13-6 Dendogram for X LIST OF FIGURES.
Page xi
Hans-Jürgen Zimmermann. Figure 13-5 Fuzzy graph . 285 Figure 13-6 Dendogram for graph - theoretic clusters . 285 Figure 13-7 The butterfly . 286 Figure 13-8 Crisp clusters of the butterfly . 287 Figure 13-9 Cluster 1 of the butterfly ...
Hans-Jürgen Zimmermann. Figure 13-5 Fuzzy graph . 285 Figure 13-6 Dendogram for graph - theoretic clusters . 285 Figure 13-7 The butterfly . 286 Figure 13-8 Crisp clusters of the butterfly . 287 Figure 13-9 Cluster 1 of the butterfly ...
Page xii
... Figure 15-6 Figure 15-7 Figure 15-8 Figure 15-9 Figure 15-10 Figure 15-11 Figure 15-12 Feasible covers . Figure 15-13 Figure 15-14 The trapezoidal form of a fuzzy number a1 = ( a ) , al , a , a ? ) . Figure 15-15 The membership function ...
... Figure 15-6 Figure 15-7 Figure 15-8 Figure 15-9 Figure 15-10 Figure 15-11 Figure 15-12 Feasible covers . Figure 15-13 Figure 15-14 The trapezoidal form of a fuzzy number a1 = ( a ) , al , a , a ? ) . Figure 15-15 The membership function ...
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