摘要
利用人工神经网络技术,建立了BP网络模型,通过网络的学习训练,比较准确地预测了粉体密相气力输送过程中的管道压降,预测准确率在93.3％以上,表明该方法可以作为密相气力输送研究中的一种有效的辅助手段。
The technology of artificial neural network is used in this paper.The back-propagation (BP) network model is also established. And the pipe pressure drop in dense-phase pneumatic conveying is predicted well by applying this network model. The result of prediction reaches more than 93.3% , which indicates that BP network can be applied as an efficient auxiliary method in study of dense-phase pneumatic conveying.
出处
《计算机与应用化学》
CAS
CSCD
北大核心
2003年第1期13-15,共3页
Computers and Applied Chemistry
基金
国家"十五"科技攻关项目(2001BA301B01)
关键词
神经网络
密相气力输送
压降
artificial neural network
dense-phase pneumatic conveying
pressure drop
