| 死端微滤牛血清白蛋白溶液膜通量的预测 |
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| 引用本文： | 王湛,席雪洁,姚金苗,宋胤,赵珊珊,王秀艳,杨丽颖,李文娟,安坤,张静,储金树.死端微滤牛血清白蛋白溶液膜通量的预测[J].北京工业大学学报,2010,36(2). |
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| 作者姓名： | 王湛 席雪洁 姚金苗 宋胤 赵珊珊 王秀艳 杨丽颖 李文娟 安坤 张静 储金树 |
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| 作者单位： | 北京工业大学环境与能源工程学院;北京流体过滤与分离技术研究中心; |
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| 基金项目： | 国家自然科学基金资助项目(20276003);;北京市自然科学基金资助项目(8052006) |
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| 摘 要： | 为实现对不同操作条件(操作压力、料液质量浓度和温度)下的牛血清白蛋白溶液死端微滤膜通量的预测,以训练步数、绝对相对误差和相关系数作为预测的衡量指标,并对所建立的3层BP神经网络和RBF神经网络基本模型的内部参数进行了优化.优化的BP神经网络模型的拓朴结构为3-9-1,学习率为0.05,学习/训练函数为traingdx,隐层到输出层的传递函数为logsig,该网络对牛血清白蛋白(BSA)溶液膜通量预测的平均绝对相对误差为2.37%,相关系数为0.9960;优化的RBF神经网络的网络设计函数为newrbe,散布常数为400,该网络对BSA溶液膜通量预测的平均绝对相对误差为4.83%,相关系数为0.987 0.结果表明,BP神经网络优于RBF神经网络.
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| 关 键 词： | 死端微滤 通量 BP神经网络 RBF神经网络 |
Predicting the Flux of BSA Solutions in the Dead-end Microfiltration |
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| WANG Zhan,XI Xue-jie,YAO Jin-miao,SONG Yin,ZHAO Shan-shan,WANG Xiu-yan,YANG Li-ying,LI Wen-juan,AN Kun,ZHANG Jing,CHU Jin-shu.Predicting the Flux of BSA Solutions in the Dead-end Microfiltration[J].Journal of Beijing Polytechnic University,2010,36(2). |
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| Authors: | WANG Zhan XI Xue-jie YAO Jin-miao SONG Yin ZHAO Shan-shan WANG Xiu-yan YANG Li-ying LI Wen-juan AN Kun ZHANG Jing CHU Jin-shu |
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| Affiliation: | 1.College of Environmental and Energy Engineering;Beijing University of Technology;Beijing 100124;China;2.Beijing Fluid Filtration & Separation Technology Research Center;Beijing 101312;China |
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| Abstract: | In order to predict the flux of BSA solutions under the different operating conditions(transmembrane pressure,feed concentration and temperature) in the dead-end microfiltration,the training epochs,correlative coefficient and relative absolute error were used as three predictive criterions,and the configurations of the developed three layers BP and RBF neural network were optimized by changing the interior parameters of neural networks.The result showed that,in the experimental rang,an optimal configuration... |
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| Keywords: | dead-end microfiltration flux BP neural network RBF neural network |
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