Research of artificial neural network algorithm based on fuzzy clustering of rough sets

被引：0
|
作者：
Chen, Yan [1 ]
Li, Taoying [1 ]
机构：
[1] Dalian Maritime Univ, Sch Econ & Management, Dalian, Liaoning, Peoples R China
来源：
DCABES 2006 Proceedings, Vols 1 and 2 | 2006年
关键词：
artificial neural network; BPNN; fuzzy clustering; fuzzy equivalent matrix; fuzzy similar matrix;
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：
BPNN (back propagation neural network) has advantages of good learning and memory, but it hasn't the ability to train samples with qualitative attributes. On the contrary, fuzzy clustering of rough sets based on fuzzy equivalent matrix has the advantage. In the paper, Fuzzy clustering of rough sets is used as anterior processor of BPNN, which is to say that firstly data records are partitioned by fuzzy clustering of rough sets and then are inputted into BPNN to be learned and memorized. BPNN model based on fuzzy clustering of rough sets and model of Multivariate Linearity Regression are both applied in costume field. By comparing the results of BPNN model with that of Multivariate Linearity Regression model, the results show that the BPNN model based on fuzzy clustering of rough sets is more effective and practical.
引用
收藏
页码：744 / 747
页数：4
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