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人工神经网络-近红外光谱法定量分析Cofrel粉末药品
引用本文:刘名扬,赵景红,张晓明,任玉林.人工神经网络-近红外光谱法定量分析Cofrel粉末药品[J].吉林大学学报(理学版),2007,45(2):301-304.
作者姓名:刘名扬  赵景红  张晓明  任玉林
作者单位:1. 清华大学 化学系, 北京 100084; 2. 辽宁出入境检验检疫局 技术中心, 辽宁省 大连 116001; 3. 吉林大学 化学学院, 长春 130012
摘    要:用人工神经网络(ANN)解析Cofrel药品的近红外(NIR)漫反射光谱, 实现了对其有效成分磷酸苯丙哌啉的精确快速定量测定. 设计了最好的ANN模型. 分别讨论了输入层和隐含层节点数对测定结果的影响. 用HPLC法的测定结果作为标准, 磷酸苯丙哌啉浓度预 测值的相对误差RE (%)<4.0%, 可以应用于Cofrel药品实际生产中的质量控制.

关 键 词:人工神经网络  近红外漫反射光谱  定量分析  科福乐  
文章编号:1671-5489(2007)02-0301-04
收稿时间:2006-05-26
修稿时间:2006年5月26日

Quantitative Analysis of Cofrel Medicines in Powder by Artificial Neural Network Method-near Infrared Spectroscopy
LIU Ming-yang,ZHAO Jing-hong,ZHANG Xiao-ming,REN Yu-lin.Quantitative Analysis of Cofrel Medicines in Powder by Artificial Neural Network Method-near Infrared Spectroscopy[J].Journal of Jilin University: Sci Ed,2007,45(2):301-304.
Authors:LIU Ming-yang  ZHAO Jing-hong  ZHANG Xiao-ming  REN Yu-lin
Institution:1. Department of Chemistry, Tsinghua University, Beijing 100084, China; 2. Centre of Technique, Liaoning Entry exit Insection and Quarantine Bureau, Dalian 116001, Liaoning Province, China; 3. College of Chemistry, Jilin University, Changchun 130012, China
Abstract:Artificial neural network(ANN) arithmetic was used to resolve near infrared (NIR) reflectance spectra of Cofrel medicine in powder.The contents of benproperine phosphate,which is effective pharmaceutical component in Cofrel medicine,has been accurately fast quantitatively predicted.The best model of ANN was designed.The effects of input nodes and hidden nodes on the results were discussed respectively.Comparison of the results with those of HPLC indicates the relative error of benproperine phosphate is less than 4.0%.The analytical result could be applied to the qualitative control of Cofrel medicines in practical manufacture.
Keywords:artificial neural network  near infrared reflectance spectra  quantitative analysis  Cofrel
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