Fuzzy set theory

被引:387
|
作者
Zimmermann, H. J. [1 ]
机构
[1] Rhein Westfal TH Aachen, Korneliusstr 5, D-52076 Aachen, Germany
关键词
fuzzy set theory; measures of fuzziness; extension principle; fuzzy data mining; fuzzy optimization;
D O I
10.1002/wics.82
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Since its inception in 1965, the theory of fuzzy sets has advanced in a variety of ways and in many disciplines. Applications of this theory can be found, for example, in artificial intelligence, computer science, medicine, control engineering, decision theory, expert systems, logic, management science, operations research, pattern recognition, and robotics. Mathematical developments have advanced to a very high standard and are still forthcoming to day. In this review, the basic mathematical framework of fuzzy set theory will be described, as well as the most important applications of this theory to other theories and techniques. Since 1992 fuzzy set theory, the theory of neural nets and the area of evolutionary programming have become known under the name of 'computational intelligence' or 'soft computing'. The relationship between these areas has naturally become particularly close. In this review, however, we will focus primarily on fuzzy set theory. Applications of fuzzy set theory to real problems are abound. Some references will be given. To describe even a part of them would certainly exceed the scope of this review. (C) 2010 John Wiley & Sons, Inc.
引用
收藏
页码:317 / 332
页数:16
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