| BP改进算法及其在乙二醇精制软测量中的应用 |
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| 引用本文： | 张磊,胡春,钱锋.BP改进算法及其在乙二醇精制软测量中的应用[J].自动化仪表,2005,26(6):31-34. |
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| 作者姓名： | 张磊 胡春 钱锋 |
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| 作者单位： | 华东理工大学自动化研究所,上海,200237 |
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| 摘 要： | 提出了一种综合改进的BP神经网络算法，该算法在训练时对不同的连接权和阈值采用不同的学习速率，由此建立了乙二醇精制塔塔釜乙二醇浓度的神经网络软测量模型。结果表明该算法能有效提高乙二醇浓度BP神经网络软测量模型的收敛精度。
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| 关 键 词： | 乙二醇 改进算法 BP神经网络算法 软测量模型 应用 综合改进 学习速率 收敛精度 醇浓度 连接权 精制塔 阈值 |
| 修稿时间： | 2004年8月4日 |
An Improved BP Algorithm and Its Application in Soft Sensing of Purifying Ethylene Glycol |
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| Zhang Lei,HU Chun,Qian Feng.An Improved BP Algorithm and Its Application in Soft Sensing of Purifying Ethylene Glycol[J].Process Automation Instrumentation,2005,26(6):31-34. |
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| Authors: | Zhang Lei HU Chun Qian Feng |
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| Affiliation: | Zhang Lei Hu Chun Qian Feng |
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| Abstract: | A comprehensively improved BP algorithm is issued in this paper. According to this algorithm, different learning rates are applied to different connection weights and threshold values when a BP network is trained. A neural network model is setup to be used on soft sensing of the concentration of the ethylene glycol of the MEG column. Practice shows that this proposed algorithm is effectively able to improve the convergence precision of the BP neural network in soft sensing for the concentration of ethylene glycol. |
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| Keywords: | BP neural network Improved algorithm Concentration of ethylene glycol Soft sensing model |
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