TITLE:
Fuzzy Regression Model Based on Fuzzy Distance Measure
AUTHORS:
Jun Deng, Qiujun Lu
KEYWORDS:
LR Fuzzy Number, LR Fuzzy Distance Measure, Mean Fuzzy Error, Fuzzy Regression
JOURNAL NAME:
Journal of Data Analysis and Information Processing,
Vol.6 No.3,
August
22,
2018
ABSTRACT: Some existed fuzzy regression methods have some special requirements for
the object of study, such as assuming the observed values as symmetric triangular
fuzzy numbers or imposing a non-negative constraint of regression
parameters. In this paper, we propose a left-right fuzzy regression method,
which is applicable to various forms of observed values. We present a fuzzy
distance and partial order between two left-right (LR) fuzzy numbers and we
let the mean fuzzy distance between the observed and estimated values as the
mean fuzzy error, then make the mean fuzzy error minimum to get the regression
parameter. We adopt two criteria involving mean fuzzy error (comparative
mean fuzzy error based on partial order) and SSE to compare the
performance of our proposed method with other methods. Finally four different
types of numerical examples are given to illustrate that our proposed
method has feasibility and wide applicability.