摘要
高炉生产过程极其复杂,给炉温状态预报带来很大困难。文章提出炉温预报中的TD-BP神经网络模型,结合模型,对众多参数的重要程度进行分析,在分析各参数相关性的基础上确定炉温预报模型的输入参数,通过计算机仿真证明,取得较好的效果。
The smelting of iron ores in a blast-furnace was a very complicated process that can make the prediction of furnace temperature difficuh. With regard to the TD BP neural network models used in predicting the furnace internal temperature, this article analyzed the respective importance of and the interrelationships between the many relating parameters. On the basis of those analyses, testing with the parameters was carried out and computer simulation had proved good results.
出处
《武汉理工大学学报》
CAS
CSCD
北大核心
2008年第8期60-62,125,共4页
Journal of Wuhan University of Technology
关键词
炉温预报
神经网络模型
参数确定
temperature of furnace
BP neural network models
select parameter
