چکیده مقاله
Polynomial regression as a special case of multiple linear regression is considered A fuzzy version of the classical polynomial regression with fuzzy output and crisp inputs is presented A neural network is constructed based on some concepts of convex optimization and stability theory, which guarantees to find the approximate parameters of the proposed model A comparison between the fuzzy polynomial regression model and two other existing models with three different well known fuzzy criteria is made The numerical results clearly showed higher accuracy of the proposed fuzzy polynomial method compared to the other fuzzy polynomial regression FPR models
کلیدواژهها
نویسندگان
Delara Karbasi
Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
Alireza Nazemi
Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
Mohammad Reza Rabiei
Faculty of Mathematical Sciences, Shahrood University of Technology, Shahrood, Iran
شیوه ارجاع
Karbasi, Delara and Nazemi, Alireza and Rabiei, Mohammad Reza,1400,Solving fuzzy polynomial regression model with neural network,Fourth International Conference on Soft Computing
ارائهشده در
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