A GOAL PROGRAMMING APPROACH TO FUZZY LINEAR REGRESSION WITH NON-FUZZY INPUT AND FUZZY OUTPUT DATA

H. Hassanpour, H. R. Maleki () and M. A. Yaghoobi
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H. Hassanpour: Department of Mathematics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, I.R. of Iran
H. R. Maleki: Faculty of Basic Sciences, Shiraz University of Technology, Shiraz, I.R. of Iran
M. A. Yaghoobi: Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, I.R. of Iran

Asia-Pacific Journal of Operational Research (APJOR), 2009, vol. 26, issue 05, 587-604

Abstract: Many researches have been carried out in fuzzy linear regression since the past three decades. In this paper, a fuzzy linear regression model based on goal programming is proposed. The proposed model takes into account the centers of fuzzy data as an important feature as well as their spreads. Furthermore, the model can deal with both symmetric and non-symmetric data. To show the efficiency of proposed model, it is compared with some earlier methods based on simulation studies and numerical examples. Moreover, the sensitivity of the model to outliers is discussed.

Keywords: Fuzzy numbers; h-level set; goal programming; linear regression (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (2)

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DOI: 10.1142/S0217595909002420

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