Adaptive arrangement classifier via neuro-fuzzy modeling

被引：0
|
作者：
Shiina, K [1 ]
机构：
[1] Waseda Univ, Tokyo 1698050, Japan
来源：
NINTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2000), VOLS 1 AND 2 | 2000年
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：
A hybrid fuzzy-neuro classifier that extracts rules in terms of polyhedrons in the input space is proposed The network uses a fuzzy disjunctive normal form in its hidden layer to effectively map polyhedral regions, which are gradually adjusted during learning to category labels The major advantage of the present method lies in that it is quite simple in architeeture, every layer enjoys a clear fuzzy logical interpretation, and the number of rules needed is very few. The results of classification experiments seem to be quite promising.
引用
收藏
页码：577 / 580
页数：4
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