改进BP网络在重组大肠杆菌高密度发酵中的应用  

Application of improved BP network in the high density fermentation of recombinant escherichia coli

作　　者：迟雷[1] 范代娣[1] 米钰[1] 

机构地区：[1]西北大学化学工程学院,陕西西安710069

出　　处：《西北大学学报（自然科学版）》2008年第2期243-247,共5页Journal of Northwest University（Natural Science Edition）

基　　金：国家自然科学基金资助项目(20476085;20606026);"863"计划基金资助项目(2006AA02Z246)

摘　　要：目的将改进BP网络应用于重组类人胶原蛋白工程菌高密度发酵过程分析。方法通过添加动量项和可变学习速度的方法对传统BP网络算法进行改进。结果确定了5-9-1的网络结构,选择15组发酵实验数据对其进行训练。改进的方法对网络的收敛起到明显效果。得到的发酵过程BP网络模型收敛性和预测性能较高,平均相对误差仅2.42%。结论该模型较传统动力学模型误差更小,更接近实验过程。Aim To apply the improved Backpropagation （BP） network in the process of high density fermentation of recombinant escherichia coli producing human-like collagen. Methods The BP network was improved by adding momentum and using variable learning rate. Results 15 Teams of data were used to train the network, whose architecture was 5-9-1. The ways by which the network was improved were clearly working. The average relative error of the BP network model was only 2. 42%, and its astringencies and predictions were nice. Conclusion The model predictions were in better agreement with the experimental data than the kinetic models.

关 键 词：BP网络 类人胶原蛋白 高密度发酵 

分 类 号：TP393[自动化与计算机技术—计算机应用技术] TU433[自动化与计算机技术—计算机科学与技术]