摘要
利用人工神经网络技术 ,建立BP网络模型 ,通过网络的学习训练 。
In this paper, the model of BP network is established by means of the artificial neural network (ANN) technology. A comparatively accurate prediction about the effect of synthetic magnesia-calcium clinker chalking rate can be obtained through the learning and training function of the network.
出处
《耐火材料》
CAS
北大核心
2001年第1期43-44,55,共3页
Refractories
关键词
BP神经网络
合成
镁钙砂
粉化率
耐火材料
BP neural network,Synthetic magnesia-calcium clinker,Chalking rate
