| 高炉铁水含硅量神经网络预测模型 |
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| 引用本文： | 李俊国,闫小林.高炉铁水含硅量神经网络预测模型[J].河北理工学院学报,2002,24(3):17-22,28. |
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| 作者姓名： | 李俊国 闫小林 |
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| 作者单位： | 河北理工学院冶金系 河北唐山063009
(李俊国)，河北理工学院冶金系 河北唐山063009(闫小林) |
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| 摘 要： | 按现代控制理论,将高炉视作多输入-单输出系统。引入人工神经网络(ANN)方法,选定若干参数作为硅含量的相关变量,建立标准的三层BP网络铁水硅预报模型。用该模型对津西5#高炉的生产数据进行离线预报,允许误差为±0.1％时命中率达到81％。
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| 关 键 词： | 高炉 铁水含硅量 神经网络预测模型 |
| 文章编号： | 1007-2829(2002)03-0017-06 |
A study on neural network prediction model of Si content in hot metal |
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| LI Jun-guo,YAN Xiao-lin.A study on neural network prediction model of Si content in hot metal[J].Journal of Hebei Institute of Technology,2002,24(3):17-22,28. |
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| Authors: | LI Jun-guo YAN Xiao-lin |
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| Institution: | LI Jun-guo,YAN Xiao-lin Department of Metallurgy,Hebei Institute of Technology,Tangshan Hebei 063009,China |
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| Abstract: | Blast furnace is regarded as a system of multi-input and single-output based on modern control theory. Artificial Neural Network has been used,several variables have been selected, and a standard three layers BP( Background Propagation) network model of silicon content pridiction is set up. With production data of No. 5 BF in JinXi Iron and Steel Co. in 2000, the off-line prediction results show that the model aims at 81% with the error of ?. 1%. |
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| Keywords: | BP neural network hot metal silicon content prediction |
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