A weighted goal programming approach to fuzzy linear regression with crisp inputs and type-2 fuzzy outputs

被引：21
|
作者：
Hosseinzadeh, E. [1 ]
Hassanpour, H. [1 ]
Arefi, M. [2 ]
机构：
[1] Univ Birjand, Fac Math Sci & Stat, Dept Math, Birjand, Iran
[2] Univ Birjand, Fac Math Sci & Stat, Dept Stat, Birjand, Iran
来源：
SOFT COMPUTING | 2015年 / 19卷 / 05期
关键词：
Type-2 fuzzy set; Linear regression; Uncertainty; Type-2 fuzzy number; Goal programming; Linguistic variable; MODEL;
D O I：
10.1007/s00500-014-1328-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Many researches have been carried out in fuzzy linear regression the past three decades. However, almost all of them are limited to type-1 fuzzy data. A fuzzy linear regression model with type-2 fuzzy output data and type-2 fuzzy coefficients is studied in this paper. A linear programming model based on goal programming is proposed to calculate the regression coefficients. To evaluate the proposed model, we present some indices based on the standard deviation, the correlation coefficient, and the standard error of estimate. The proposed method is illustrated by some numerical examples.
引用
收藏
页码：1143 / 1151
页数：9
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