A new parameter selection method of neural network

被引：1
|
作者：
Wu, Gui-Fang [1 ,2 ]
Jang, Se-young [1 ]
Kwak, Hoon-sung [1 ]
Pu, Jie-xin [2 ]
机构：
[1] Chonbuk Natl Univ Korea, Coll Engn, Dept Comp Engn, Jeonju 561756, South Korea
[2] Henan Univ Technol, Elect & Informat Engn Dept, Dept Automat, Luoyang, Peoples R China
来源：
MUE: 2008 INTERNATIONAL CONFERENCE ON MULTIMEDIA AND UBIQUITOUS ENGINEERING, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/MUE.2008.99
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
A new parameter selection method of neural network is presented after researching parameter selection method of neural network deeply, and it is applied to surface defect online inspection system Of cold rolled strips. The method exerted the merits of small-samples fully which was utilized to train and test neural network by every possible combination of parameters to get a group of neural network parameters by plotting histogram of recognition rate under different parameter combinations, and the parameters are regarded as optimized parameters of neural network. Experiments showed that a best recognition effect by using the parameters for neural network which are selected by the new parameter selection method can be achieved among all the parameters selected randomly for surface defect of cold rolled strips.
引用
收藏
页码：378 / +
页数：2
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