BP改进算法及其在乙二醇精制软测量中的应用

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。
关键词BP 神经网络算法改进乙二醇浓度软测量模型
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.
Keywords BP neural network Improved algorithm Concentration of ethylene glycol Soft sensing model