Fuzzy Linear Regression Models with Fuzzy Entropy
نویسنده
چکیده
Fuzzy regression analysis using fuzzy linear models with symmetric triangular fuzzy number coefficient has been introduced by Tanaka et al. The goal of this regression is to find the coefficient of a proposed model for all given input-output data sets. In this paper, we propose a new 1716 E. Pasha et al method for computation of fuzzy regression. The method is constructed on the basis of minimizing the fuzzy entropy of predicted values. The advantage of the propose approach depend on the entropy's properties to rectify previous problems in fuzzy linear regression with crisp input and fuzzy output. To compare the performance of the proposed approach with the other methods, an example is presented.
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