Article ID: | iaor1989638 |
Country: | Netherlands |
Volume: | 40 |
Issue: | 3 |
Start Page Number: | 389 |
End Page Number: | 396 |
Publication Date: | Jun 1989 |
Journal: | European Journal of Operational Research |
Authors: | Tanaka Hideo, Hayashi Isao |
Keywords: | statistics: regression |
Fuzzy data given by expert knowledge can be regarded as a possibility distribution by which possibilistic linear systems are defined. Recently, it has become important to deal with fuzzy data in connection with expert knowledge. Three formulations of possibilistic linear regression analysis are proposed here to deal with fuzzy data. Since the present formulations can be reduced to linear programming problems, the merit of the formulations is to be able to obtain easily fuzzy parameters in possibilistic linear models and to add other constraint conditions which might be obtained from expert knowledge of fuzzy parameters. This approach can be regarded as a fuzzy interval analysis in a fuzzy environment.