Fuzzy regression analysis by entropy

被引:1
作者
Kao, C [1 ]
Lin, PH [1 ]
机构
[1] Natl Cheng Kung Univ, Dept Ind & Informat Management, Tainan 70101, Taiwan
来源
2004 2ND INTERNATIONAL IEEE CONFERENCE INTELLIGENT SYSTEMS, VOLS 1 AND 2, PROCEEDINGS | 2004年
关键词
entropy; fuzzy sets; regression; least-squares method;
D O I
10.1109/IS.2004.1344672
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To construct a regression model for fuzzy numbers, this paper decomposes a fuzzy number into two parts: the position and fuzziness. The former is represented by the elements with membership value 1 and the latter by the entropy of the fuzzy number, both have crisp values. The conventional regression analysis is applied to find the relationship between the position (and entropy) of the fuzzy response variable and that of the fuzzy explanatory variables. Given a set of fuzzy explanatory variables, the position and entropy of the,estimated fuzzy responses are calculated from the regression model. Via the one-to-one correspondence between a fuzzy number and its entropy, the estimated fuzzy response is obtained.
引用
收藏
页码:231 / 236
页数:6
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