摘要
对高炉铁水硅含量预报的统计模型、神经网络模型和神经网络方法加统计方法的综合模型三种预报模型作了对比 ,结果表明 :用神经网络方法和统计模型综合预报的效果较好 ,离线模型预报结果± 0 .1命中率达到 86 .6 7 。
A kind of comprehensive model based on neural networks and statistics models has been compared with the statistics model and the neural networks model.The results show that the comprehensive model performs best,the accuracy of ±0 1 aims at 86 67 %.It's a good application of neural networks to predict Si content of hot metal
出处
《钢铁》
CAS
CSCD
北大核心
2001年第5期14-16,共3页
Iron and Steel
关键词
高炉
硅含量预报
神经网络
统计模型
炼铁
blast furnace
Si content
prediction
neural networks
statistics model
