Fuzzy C-Regression Models

Yan Hua Yu; Li Xia Song; Kun Lun Zhang

doi:10.4028/www.scientific.net/AMM.278-280.1323

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 278-280Fuzzy C-Regression Models

Fuzzy C-Regression Models

Abstract:

Fuzzy linear regression has been extensively studied since its inception symbolized by the work of Tanaka et al. in 1982. As one of the main estimation methods, fuzzy least squares approach is appealing because it corresponds, to some extent, to the well known statistical regression analysis. In this article, a restricted least squares method is proposed to fit fuzzy linear models with crisp inputs and symmetric fuzzy output. The paper puts forward a kind of fuzzy linear regression model based on structured element, This model has precise input data and fuzzy output data, Gives the regression coefficient and the fuzzy degree function determination method by using the least square method, studies the imitation degree question between the observed value and the forecast value.

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Periodical:

Applied Mechanics and Materials (Volumes 278-280)

Pages:

1323-1326

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.278-280.1323

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Online since:

January 2013

Authors:

Yan Hua Yu, Li Xia Song, Kun Lun Zhang

Keywords:

C-Regression Models, Fuzzy C-Regression Models, Fuzzy Set

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