Fuzzy polynomial regression with fuzzy neural networks

被引：26
|
作者：
Mosleh, M. [2 ]
Otadi, M. [2 ]
Abbasbandy, S. [1 ]
机构：
[1] Islamic Azad Univ, Sci & Res Branch, Dept Math, Tehran, Iran
[2] Islamic Azad Univ, Firoozkooh Branch, Dept Math, Firoozkooh, Iran
来源：
APPLIED MATHEMATICAL MODELLING | 2011年 / 35卷 / 11期
关键词：
Neural network; Fuzzy polynomial regression model; Learning algorithm; NUMERICAL-SOLUTION; MODEL; WEIGHTS;
D O I：
10.1016/j.apm.2011.04.039
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Recently, fuzzy linear regression is considered by Mosleh et al. [1]. In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy polynomial regression models with fuzzy output and crisp inputs, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码：5400 / 5412
页数：13
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