Fully fuzzy polynomial regression with fuzzy neural networks

被引：27
|
作者：
Otadi, Mahmood [1 ]
机构：
[1] Islamic Azad Univ, Dept Math, Firoozkooh Branch, Firoozkooh, Iran
来源：
NEUROCOMPUTING | 2014年 / 142卷
关键词：
Fuzzy regression; Fuzzy neural networks; Learning algorithm; POSSIBILISTIC LINEAR-SYSTEMS; DIFFERENTIAL-EQUATIONS; NUMERICAL-SOLUTION; OUTPUT DATA; MODEL; SIMULATION; WEIGHTS; INPUT;
D O I：
10.1016/j.neucom.2014.03.048
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper a polynomial fuzzy regression model with fuzzy independent variables and fuzzy parameters is discussed. Within this paper the fuzzy neural network model is used to obtain an estimate for the fuzzy parameters in a statistical sense. Based on the extension principle, a simple algorithm from the cost function of the fuzzy neural network is proposed, in order to find the approximate parameters. Finally, we illustrate our approach by some numerical examples. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码：486 / 493
页数：8
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