| 利用人工神经网络预测热连轧精轧机组带钢宽度变化 |
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| 引用本文： | 吕程 谷立军. 利用人工神经网络预测热连轧精轧机组带钢宽度变化[J]. 上海金属, 1998, 20(4): 36-39 |
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| 作者姓名： | 吕程 谷立军 |
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| 作者单位： | 东北大学!110006(吕程，王国栋，刘相华)，上海宝山钢铁（集团）公司(谷立军) |
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| 摘 要： | 采用BP神经网络方法代替传统的数学模型预测精轧机组轧制带钢的宽度变化，以提高热轧带钢的宽度精度，并进行了不同网络结构的比较研究。结果表明，BP神经网络方法优于传统数学模型方法，其预测值与实测值的标准差减小了51．9％。
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| 关 键 词： | 热连轧 宽度变化预测 BP神经网络 |
PREDICTING THE WIDTH VARIATION OF STRIP IN THE FINISHING STAND BY ARTIFICIAL NEURAL NETWORKS |
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| Lu Cheng,Wang Guodong, Liu Xianghua. PREDICTING THE WIDTH VARIATION OF STRIP IN THE FINISHING STAND BY ARTIFICIAL NEURAL NETWORKS[J]. Shanghai Metals, 1998, 20(4): 36-39 |
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| Authors: | Lu Cheng Wang Guodong Liu Xianghua |
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| Affiliation: | Lu Cheng;Wang Guodong; Liu Xianghua(Northeastern University)Gu Lijun(Baoshan Iron and Steel Corp. )[ |
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| Abstract: | in Qrder to increase the width precision of hot rolled strip, the BP neural networks is used to predict the width variation of strip in the finishing stand instead of the traditional mathematics model,and the research comparison on the different structures of BP neural networks is executed. The results show that the prediction of BP neural networks is better than that of the mathematical model, the standard deviation of BP neural networks decreases by 51. 9%[ |
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| Keywords: | Hot Continuous Rolling Prediction of Width Variation BP Neural Networks |
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