Fuzzy Least Squares Estimation with New Fuzzy Operations

被引：0
|
作者：
Yoon, Jin Hee [1 ]
Choi, Seung Hoe [2 ]
机构：
[1] Yonsei Univ, Sch Econ, Seoul 120749, South Korea
[2] Korea Aerosp Univ, Sch Liberal Arts & Sci, Koyang 412791, South Korea
来源：
SYNERGIES OF SOFT COMPUTING AND STATISTICS FOR INTELLIGENT DATA ANALYSIS | 2013年 / 190卷
关键词：
Fuzzy least squares estimator; fuzzy random variable; triangular fuzzy matrix; LINEAR-REGRESSION ANALYSIS; INPUT-OUTPUT DATA; MODELS; PARAMETERS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper deals with fuzzy least squares estimation of the fuzzy linear regression model with fuzzy input-output data that has an error structure. The paper proposes fuzzy least squares estimators (FLSEs) for regression parameters based on a suitable metric, and shows that the estimators are fuzzy-type linear estimators. To find these estimators, we first defined a notion of triangular fuzzy matrices whose elements are given as triangular fuzzy numbers, and also provided some operations among all triangular fuzzy matrices. Simple computational examples of this applications are given.
引用
收藏
页码：193 / +
页数：3
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