چکیده مقاله
In this paper, a fuzzy linear regression model with triangular interval valued fuzzy output and inputs is presented The presented mathematical formulation of the model leads to a non differentiable program which is converted to an equivalent convex problem by using an appropriate well known method In order to approximate interval valued fuzzy coefficients a hybrid scheme based on recurrent neural networks is introduced A real data sets, on hydrology is used to test the applicability of the proposed method The predictive ability of the model thus obtained is examined by cross validation
کلیدواژهها
نویسندگان
Delara Karbasi
Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
Mohammad Reza Rabiei
Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
Alireza Nazemi
Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
شیوه ارجاع
Karbasi, Delara and Rabiei, Mohammad Reza and Nazemi, Alireza,1400,Numerical solution of fuzzy interval-valued regression model by neural network,Fourth International Conference on Soft Computing
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