Fuzzy Regression Models
نویسنده
چکیده
Recent articles, such as McCauley-Bell et al. (1999) and Sánchez and Gómez (2003a, 2003b, 2004), used fuzzy regression (FR) in their analysis. Following Tanaka et. al. (1982), their regression models included a fuzzy output, fuzzy coefficients and an nonfuzzy input vector. The fuzzy components were assumed to be triangular fuzzy numbers (TFNs). The basic idea was to minimize the fuzziness of the model by minimizing the total support of the fuzzy coefficients, subject to including all the given data. The purpose of this article is to revisit the fuzzy regression portions of the foregoing studies and to discuss issues related to the Tanaka approach, including a consideration of fuzzy least-squares regression models.
منابع مشابه
Two Robust Fuzzy Regression Models and Their Applications in Predicting Imperfections of Cotton Yarn
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