A NOTE ON EVALUATION OF FUZZY LINEAR REGRESSION MODELS BY COMPARING MEMBERSHIP FUNCTIONS

Kim and Bishu (Fuzzy Sets and Systems 100 (1998) 343-352) proposed a modification of fuzzy linear regression analysis. Their modification is based on a criterion of minimizing the difference of the fuzzy membership values between the observed and estimated fuzzy numbers. We show that their method of...

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Bibliographic Details
Published in:Iranian journal of fuzzy systems (Online) 2009-06, Vol.6 (2), p.1
Main Authors: Hassanpour, H, Malek, H R, Yaghoobi, M A
Format: Article
Language:English
Subjects:
Fuzzy sets
Regression analysis
Online Access:Get full text
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Summary:Kim and Bishu (Fuzzy Sets and Systems 100 (1998) 343-352) proposed a modification of fuzzy linear regression analysis. Their modification is based on a criterion of minimizing the difference of the fuzzy membership values between the observed and estimated fuzzy numbers. We show that their method often does not find acceptable fuzzy linear regression coefficients and to overcome this shortcoming, propose a modification. Finally, we present two numerical examples to illustrate efficiency of the modified method.
ISSN:1735-0654
2676-4334
DOI:10.22111/ijfs.2009.203