Extended fuzzy linear models and least squares estimates

被引：90

作者：

Diamond, P ^{[1
]}

Korner, R ^{[1
]}

机构：

[1] FREIBERG UNIV MIN & TECHNOL,FAC MATH & COMP SCI,D-09596 FREIBERG,GERMANY

来源：

COMPUTERS & MATHEMATICS WITH APPLICATIONS | 1997年 / 33卷 / 09期

关键词：

fuzzy linear regression; least squares estimates; Hukuhara difference;

D O I：

10.1016/S0898-1221(97)00063-1

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Least squares regression of the Fuzzy linear model is extended to overcome and interpret the occurrence of negative spreads tl]. The idea is to introduce best fit difference models which exploit both the Hukuhara difference and the L-2-metric distance. The fuzzy models use LR-fuzzy numbers. Fitted models are compared by using the coefficient of determination, in a similar way to its use in classical statistical least squares fitting. The non-LR-fuzzy case is also considered.

引用

页码：15 / 32

页数：18

共 13 条

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