摘要
以理论模型为基础,建立了转炉炼钢静态控制模型,并将人工神经网络模型应用到转炉控制中,以Visual Basic为开发语言,开发了相应的软件。通过BP神经网络预报了终点的碳含量,当碳命中误差±0.02%时,命中率达到了66.7%。
On the basis of theoretical model is established a converter static control model, in which the artificial neural network is applied to control the converter operation. Corresponding software has been developed using the visual basic as the development language. The hitting rate attains 66. 7 % and deviation of the hitting rate is controlled within ± 0. 02 % when predicting the end point C content by BP neural network.
出处
《炼钢》
CAS
北大核心
2006年第6期41-44,共4页
Steelmaking
关键词
转炉炼钢
静态模型
BP网络
converter steel-making
static model
BP neural net
