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. |
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Page iv
... means , mechanical , photocopying , recording , or otherwise , without the prior written permission of the publisher , Springer Science + Business Media , LLC Printed on acid - free paper . 1 1.1 1.2 List of Figures List of Tables Foreword.
... means , mechanical , photocopying , recording , or otherwise , without the prior written permission of the publisher , Springer Science + Business Media , LLC Printed on acid - free paper . 1 1.1 1.2 List of Figures List of Tables Foreword.
Page xi
... means . 315 Figure 13-26 Structure of DataEngine . 318 Figure 13-27 Screen shot of DataEngine . 320 Figure 13-28 Cracking furnace . 324 Figure 13-29 Furnace temperature . 325 Figure 13-30 Fuzzy classification of continuous process . 325 ...
... means . 315 Figure 13-26 Structure of DataEngine . 318 Figure 13-27 Screen shot of DataEngine . 320 Figure 13-28 Cracking furnace . 324 Figure 13-29 Furnace temperature . 325 Figure 13-30 Fuzzy classification of continuous process . 325 ...
Page xii
... mean operator . Predicted vs. observed data : y - operator . 473 474 Figure 16-16 Concept hierarchy of creditworthiness together with individual weights d and g - values for each level of aggregation . 475 Table 3-1 operators . Table 3 ...
... mean operator . Predicted vs. observed data : y - operator . 473 474 Figure 16-16 Concept hierarchy of creditworthiness together with individual weights d and g - values for each level of aggregation . 475 Table 3-1 operators . Table 3 ...
Page 1
... mean dichotomous , that is , yes - or - no - type rather than more - or - less type . In conventional dual logic , for instance , a statement can be true or false — and nothing in between . In set theory , an element can either belong ...
... mean dichotomous , that is , yes - or - no - type rather than more - or - less type . In conventional dual logic , for instance , a statement can be true or false — and nothing in between . In set theory , an element can either belong ...
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... means as 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 ...
... means as 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 ...
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