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A NOTE ON EVALUATION OF FUZZY LINEAR REGRESSION MODELS BY COMPARING MEMBERSHIP FUNCTIONS | ||
| Iranian Journal of Fuzzy Systems | ||
| مقاله 2، دوره 6، شماره 2، شهریور 2009، صفحه 1-6 اصل مقاله (143.52 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22111/ijfs.2009.203 | ||
| نویسندگان | ||
H. Hassanpour 1؛ H. R. Malek  2؛ M. A. Yaghoobi3
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| 1Department of Mathematics, University of Birjand, Birjand, Iran | ||
| 2Faculty of Basic Sciences, Shiraz University of Technology, Shiraz, Iran | ||
| 3Department of Statistics, Shahid Bahonar University of Kerman, Kerman, Iran | ||
| چکیده | ||
| 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. | ||
| کلیدواژه‌ها | ||
| Fuzzy linear regression؛ Fuzzy number؛ Least-squares method. This paper is supported in part by Fuzzy Systems and Applications Center of Excellence؛ Shahid Bahonar University of Kerman؛ Kerman؛ I.R. of Iran | ||
| مراجع | ||
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