A WEIGHTED GOAL PROGRAMMING APPROACH TO FUZZY LINEAR REGRESSION WITH QUASI TYPE-2 FUZZY INPUT-OUTPUT DATA

被引：0
|
作者：
Hosseinzadeh, E. [1 ]
Hassanpour, H. [1 ]
Arefi, M. [2 ]
Aman, M. [1 ]
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：
TWMS JOURNAL OF APPLIED AND ENGINEERING MATHEMATICS | 2016年 / 6卷 / 02期
关键词：
fuzzy linear regression; goal programming; type-2 fuzzy set; uncertainty; quasi type-2; fuzzy number;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This study attempts to develop a regression model when both input data and output data are quasi type-2 fuzzy numbers. To estimate the crisp parameters of the regression model, a linear programming model is proposed based on goal programming. To handle the outlier problem, an omission approach is proposed. This approach examines the behavior of value changes in the objective function of proposed model when observations are omitted. In order to illustrate the proposed model, some numerical examples are presented. The applicability of the proposed method is tested on a real data set on soil science. The predictive performance of the model is examined by cross-validation.
引用
收藏
页码：193 / 212
页数：20
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