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 xxi
... chapters have been updated . Chapters 9 , 10 , 11 , and 12 have been completely rewritten . Nevertheless , I have tried not to let the book grow beyond a basic textbook . To ... chapter 11 , and all my Preface to the Third Edition.
... chapters have been updated . Chapters 9 , 10 , 11 , and 12 have been completely rewritten . Nevertheless , I have tried not to let the book grow beyond a basic textbook . To ... chapter 11 , and all my Preface to the Third Edition.
Page xxii
Hans-Jürgen Zimmermann. butions , particularly to chapter 11 , and all my coworkers for helping to proofread the book and to prepare new figures . We all hope that this third edition will benefit future students and accelerate the ...
Hans-Jürgen Zimmermann. butions , particularly to chapter 11 , and all my coworkers for helping to proofread the book and to prepare new figures . We all hope that this third edition will benefit future students and accelerate the ...
Page xxiv
... chapter on data mining and a new chapter on fuzzy sets in data bases . The following figure indicates the development of fuzzy set theory from another point of view : Academic Stage Consolidation and Integration Theory Survey of ...
... chapter on data mining and a new chapter on fuzzy sets in data bases . The following figure indicates the development of fuzzy set theory from another point of view : Academic Stage Consolidation and Integration Theory Survey of ...
Page xxv
... chapter 10 the modeling of uncertainty in expert systems was extended because this component has gained importance in practice . In chapter 11 primarily a section for defuzzification has been added for the same reason . Chapter 12 has ...
... chapter 10 the modeling of uncertainty in expert systems was extended because this component has gained importance in practice . In chapter 11 primarily a section for defuzzification has been added for the same reason . Chapter 12 has ...
Page 5
... chapter 8 . In chapter 16 we will return to this figure and elaborate on the type of aggregation . 1.2 Fuzzy Set Theory The first publications in fuzzy set theory by Zadeh [ 1965 ] and Goguen [ 1967 , 1969 ] show the intention of the ...
... chapter 8 . In chapter 16 we will return to this figure and elaborate on the type of aggregation . 1.2 Fuzzy Set Theory The first publications in fuzzy set theory by Zadeh [ 1965 ] and Goguen [ 1967 , 1969 ] show the intention of the ...
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