Evaluation of Fuzzy Linear Regression Models by Parametric Distance
نویسندگان
چکیده
Fuzzy linear regression models can provide an estimated fuzzy number that has a fuzzy membership function. If a point that has the highest membership value from the estimated fuzzy number is not within the support of the observed fuzzy membership function, a decisionmaker can have high risk from the estimate. In this study a new distance, between fuzzy numbers is proposed. On the basis of this distance a fuzzy least square regression model is constructed for the case of polynomial-type dependent variable and ordinary input variables.
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