| 粗轧过程轧制力BP神经网络预报 |
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| 引用本文： | 张凤琴,刘娟,徐建忠,刘相华,王国栋. 粗轧过程轧制力BP神经网络预报[J]. 上海金属, 2004, 26(4): 38-40 |
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| 作者姓名： | 张凤琴 刘娟 徐建忠 刘相华 王国栋 |
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| 作者单位： | 东北大学轧制技术及连轧自动化国家重点实验室,沈阳市,110004;东北大学轧制技术及连轧自动化国家重点实验室,沈阳市,110004;东北大学轧制技术及连轧自动化国家重点实验室,沈阳市,110004;东北大学轧制技术及连轧自动化国家重点实验室,沈阳市,110004;东北大学轧制技术及连轧自动化国家重点实验室,沈阳市,110004 |
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| 摘 要： | 利用BP神经网络 ,以某热轧厂粗轧机组数据库中的数据为训练样本 ,采用两种训练方案 ,对粗轧过程轧制力进行预测。BP网络的预报精度 ,既与训练样本的选取有关 ,又与隐层节点的个数以及相对化系数的大小有着密切的联系。以上因素选取得当 ,能够提高网络的预报精度 ,若选取不当 ,则降低网络的预报精度
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| 关 键 词： | 带钢粗轧 轧制力预报 BP神经网络 神经元 |
| 修稿时间： | 2003-09-28 |
PREDICTION OF ROUGH ROLLING FORCE BY BP NEURAL NETWORKS |
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| Zhang Fengqin Liu juan Xu Jianzhong Liu Xianghua Wang Guodong. PREDICTION OF ROUGH ROLLING FORCE BY BP NEURAL NETWORKS[J]. Shanghai Metals, 2004, 26(4): 38-40 |
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| Authors: | Zhang Fengqin Liu juan Xu Jianzhong Liu Xianghua Wang Guodong |
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| Affiliation: | Northeastern University |
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| Abstract: | Based on the measured data from a hot strip mill, the rolling force in roughing was predicted by means of BP neural networks which adopted two kinds of training methods. It was proved that the prediction accuracy of BP neural networks was not only relating to the choosing of the training patterns but also the number of the hidden layer and the relativation coefficient. The neural networks prediction accuracy could be improved if the above parameters were set advisably, or else the accuracy would decrease. |
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| Keywords: | Strip Roughing Rolling Force Prediction BP neural Networks Neuron |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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