Neuro-fuzzy relational classifiers

被引：0
|
作者：
Scherer, R
Rutkowski, L
机构：
[1] Czestochowa Tech Univ, Dept Comp Engn, PL-42200 Czestochowa, Poland
[2] Univ Lodz, WSHE, Dept Artificial Intelligence, PL-90131 Lodz, Poland
来源：
ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING - ICAISC 2004 | 2004年 / 3070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：
In the paper, we present a new fuzzy relational system with multiple outputs for classification purposes. Rules in the system are more flexible than the rules in linguistic fuzzy systems because of the additional weights in rule consequents. The weights comes from an additional binary relation. Thanks to this, input and output fuzzy sets are related to each other with a certain degree. The size of the relations is determined by the number of input fuzzy sets and the number of output fuzzy sets for a given class. Simulation results confirmed the system ability to classify data.
引用
收藏
页码：376 / 380
页数：5
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