摘要
为了提高辊底式热处理炉的钢板温度预报精度,采用了遗传神经网络的方法,运用大量的现场实际数据进行训练和仿真,建立了钢板温度预报模型,并将结果应用于计算辊底式热处理炉钢板温度的数学模型中。结果表明,所建立的模型简单、精度高,能够满足在线应用的要求。
In order to improve the steel plate temperature prediction accuracy of the roller-hearth heat treatment furnace, GA-BP neural network is trained by a great deal of actual data. The model is used to calculate the steel plate temperature of the roller-hearth heat treatment furnace. The result shows that the model is very simple and it has high precision and satisfies the actual application.
出处
《钢铁研究学报》
CAS
CSCD
北大核心
2008年第4期30-33,共4页
Journal of Iron and Steel Research
关键词
辊底式热处理炉
温度预报
遗传神经网络
roller-hearth heat treatment furnace
temperature prediction
genetic neural network
