Fuzzy linear regression analysis for fuzzy input-output data using shape-preserving operations

被引：35

作者：

Hong, DH

Lee, S

Do, HY

机构：

[1] Catholic Univ Taegu Hyosung, Sch Mech & Automot Engn, Kyungbuk 712702, South Korea

[2] Taegu Univ, Dept Stat, Taegu 712714, South Korea

[3] Kyungpook Natl Univ, Dept Stat, Taegu 702701, South Korea

来源：

FUZZY SETS AND SYSTEMS | 2001年 / 122卷 / 03期

关键词：

fuzzy linear regression; fuzzy input-output data; shape-preserving operations;

D O I：

10.1016/S0165-0114(00)00003-8

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, we have presented a new method to evaluate fuzzy linear regression models based on Tanaka's approach, where both input data and output data are fuzzy numbers, using T-w-based fuzzy arithmetic operations. This method simplifies the computation of fuzzy arithmetic operations. General linear program is applied to derive the solutions. We also prove scale-independent property of our models and discuss the effects of outliers. (C) 2001 Elsevier Science B.V. All rights reserved.

引用

页码：513 / 526

页数：14

共 19 条

[1] LEAST-SQUARES MODEL-FITTING TO FUZZY VECTOR DATA [J].