A method about load distribution of rolling mills based on RBF neural network

被引：0

作者：

Liu, Dong Dong ^{[1
]}

机构：

[1] LinYi Univ, Coll Engn, Linyi, Shandong, Peoples R China

来源：

MECHANICS, SOLID STATE AND ENGINEERING MATERIALS | 2011年 / 279卷

关键词：

RBF neural networks; prediction of thickness; prediction of rolling force; load distribution; hot strip mills;

D O I：

10.4028/www.scientific.net/AMR.279.418

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Rolling mills process is too complicated to be described by formulas. RBF neural networks can establish finishing thickness and rolling force models. Traditional models are still useful to the neural network output. Compared with those finishing models which have or do not have traditional models as input, the importance of traditional models in application of neural networks is obvious. For improving the predictive precision, BP and RBF neural networks are established, and the result indicates that the model of load distribution based on RBF neural network is more accurate.

引用

页码：418 / 422

页数：5