Modular type-2 neuro-fuzzy systems

被引：0
|
作者：
Starczewski, Janusz [1 ]
Scherer, Rafal [1 ]
Korytkowski, Marcin [1 ]
Nowicki, Robert [1 ]
机构：
[1] Czestochowa Tech Univ, Dept Comp Engn, PL-42200 Czestochowa, Poland
来源：
PARALLEL PROCESSING AND APPLIED MATHEMATICS | 2008年 / 4967卷
关键词：
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
In the paper we study a modular system which can be converted into a type-2 neuro-fuzzy system. The rule base of such system consists of triangular type-2 fuzzy sets. The modular structure is trained using the backpropagation method combined with the AdaBoost algorithm. By applying the type-2 neuro-fuzzy system, the modular structure is converted into a compressed form. This allows to overcome the training problem of type-2 neuro-fuzzy systems. An illustrative example is given to show the efficiency of our approach in the problems of classification.
引用
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页码：570 / 578
页数：9
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