A multilayer feedforward fuzzy neural network

被引：0
|
作者：
Savran, Aydogan [1 ]
机构：
[1] Ege Univ, Dept Elect & Elect Engn, TR-35100 Izmir, Turkey
来源：
ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS | 2006年 / 3949卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes the architecture and learning procedure of a multilayer feedforward fuzzy neural network (FNN). The FNN is designed by replacing the sigmoid type activation function of the multilayer neural network (NN) with the fuzzy system (FS). The Levenberg-Marquardt (LM) optimization method with a trust region approach is adapted to train the FNN. Simulation results of a non-linear system identification problem are given to show the validity of the approach.
引用
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页码：78 / 83
页数：6
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