人工神经网络紫外分光光度法同时测定去痛片组分含量  

Simultaneous Determination of Individual Medicaments in Anodyne Tablets by Artificial Neural Networks and Ultraviolet Spectrophotometry

作　　者：陈振宁[1] 

机构地区：[1]哈尔滨工业大学应用化学系,哈尔滨150001

出　　处：《分析化学》2001年第11期1322-1324,共3页Chinese Journal of Analytical Chemistry

摘　　要：用BP人工神经网络处理复方制剂去痛片的紫外吸收光谱数据 ,达到了对其各组分含量进行同时测定的目的。通过对网络结构和参数的优化 。The back propagation artificial neural network (BPANN) was applied to process UV spectrophotometric data of anodyne tablets. By optimizing the network structure and parameters, the predication accuracy was enhanced. The measure of preventing the network overfitting and avoiding local minimum points was also taken. The method has been applied to the simultaneous determination of individual medicaments in anodyne tablets.

关 键 词：人工神经网络 紫外分光光度法 去痛片 药物含量测定 

分 类 号：O657.3[理学—分析化学]