2006 | OriginalPaper | Buchkapitel
Fuzzy Regression Approaches and Applications
verfasst von : Cengiz Kahraman, Ahmet Beşkese, F. Tunç Bozbura
Erschienen in: Fuzzy Applications in Industrial Engineering
Verlag: Springer Berlin Heidelberg
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Fuzzy regression is a fuzzy variation of classical regression analysis. It has beenstudied and applied to various areas. Two types of fuzzy regression models are Tanaka’s linear programming approach and the fuzzy least-squares approach. In this chapter, a wide literature review including both theoretical and application papers on fuzzy regression has been given. Fuzzy regression models for nonfuzzy input/nonfuzzy output, nonfuzzy input/fuzzy output, and possibilistic regression model have been summarized. An illustrative example has been given. Fuzzy hypothesis testing for the coefficients of a linear regression function has been explained with two numerical examples.