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 37
Page xv
Professor Zimmermann's treatise provides an affirmative answer to this question. His comprehensive exposition of both the theory and its applications explains in clear terms the basic concepts that underlie the theory and how they ...
Professor Zimmermann's treatise provides an affirmative answer to this question. His comprehensive exposition of both the theory and its applications explains in clear terms the basic concepts that underlie the theory and how they ...
Page xvi
And, most importantly, it succeeds in providing an excellent introduction to the theory of fuzzy sets—an introduction that makes it possible for an uninitiated reader to obtain a clear view of the theory and learn about its applications ...
And, most importantly, it succeeds in providing an excellent introduction to the theory of fuzzy sets—an introduction that makes it possible for an uninitiated reader to obtain a clear view of the theory and learn about its applications ...
Page xvii
The primary goal of this book is to help to close this gap—to provide a textbook for courses in fuzzy set theory and a book that can be used as an introduction. One of the areas in which fuzzy sets have been applied most extensively is ...
The primary goal of this book is to help to close this gap—to provide a textbook for courses in fuzzy set theory and a book that can be used as an introduction. One of the areas in which fuzzy sets have been applied most extensively is ...
Page xviii
It is intended to provide extensive coverage of the theoretical and applicational approaches to fuzzy sets. Sophisticated formalisms have not been included. I have tried to present the basic theory and its extensions in enough detail to ...
It is intended to provide extensive coverage of the theoretical and applicational approaches to fuzzy sets. Sophisticated formalisms have not been included. I have tried to present the basic theory and its extensions in enough detail to ...
Page xxi
In addition, the transition from fuzzy set theory to fuzzy technology has been achieved by providing numerous software and hardware tools that considerably improve the design of fuzzy systems and make them more applicable in practice.
In addition, the transition from fuzzy set theory to fuzzy technology has been achieved by providing numerous software and hardware tools that considerably improve the design of fuzzy systems and make them more applicable in practice.
What people are saying - Write a review
We haven't found any reviews in the usual places.
Contents
9 | |
11 | |
16 | |
22 | |
29 | |
Criteria for Selecting Appropriate Aggregation Operators | 43 |
The Extension Principle and Applications | 54 |
Special Extended Operations | 61 |
Applicationoriented Modeling of Uncertainty | 111 |
Linguistic Variables | 140 |
Fuzzy Data Bases and Queries | 265 |
Decision Making in Fuzzy Environments | 329 |
Applications of Fuzzy Sets in Engineering and Management | 371 |
Empirical Research in Fuzzy Set Theory | 443 |
Future Perspectives | 477 |
181 | 485 |
Other editions - View all
Common terms and phrases
aggregation algorithm analysis applications approach appropriate approximately areas assignment assume base called chapter classical clustering compute concepts considered constraints contains corresponding crisp criteria customers decision defined definition degree of membership depends described determine discussed distribution domain elements engineering example exist expert systems expressed extension Figure fuzzy control fuzzy numbers fuzzy set theory given goal human important indicate inference input instance integral interpreted intersection interval knowledge linguistic variable logic mathematical mean measure membership function methods normally objective objective function observed obtain operators optimal positive possible probability problem programming properties provides reasoning relation representing require respect rules scale shown shows similarity situation solution space specific statement structure suggested t-norms Table tion true truth uncertainty values Zadeh