人工神经网络紫外光谱法测定氯芬待因片含量  

The Artifical Neural Networks Spectrophotometry Used in Simultaneous Determination of Two Ingredients in Shuerfen Tablet

作　　者：徐楚鸿[1] 张江兰[1] 吕永宁[1] 王虎[1] 

机构地区：[1]华中科技大学同济医学院附属协和医院药剂科,武汉430022

出　　处：《医药导报》2003年第9期640-641,共2页Herald of Medicine

摘　　要：目的 :对紫外光谱重叠的氯芬待因片进行多组分不经分离的含量测定。方法 :应用前向型误差反向传播人工神经网络对氯芬待因片进行含量测定。结果 :3个模拟样品平均回收率和RSD分别为磷酸可待因 98.68% ,3 .40 % ;双氯芬酸钠 10 0 .0 1% ,0 .94%。结论 :该方法测定结果准确 ,性能良好 ,对于吸收光谱重叠的药物含量测定有一定的参考价值。Objective:To determine the concentration of the contents of shuerfen tablets which UV spectrum are overlapped. Method:The error back-propagation(BP) method of artifical neural networks(ANN) has been used to determine codeine phosphate and diclofenac sodium without separating them. In 400-190 nm, the absorbance at 9 wavelength was taken as character parameter of ANN,and samples value were input. Results:The average recoveries and relative standard deviations of two components in three model samples were 98.68%, 3.40% for codeine phosphate and 100.01%, 0.94% for diclofenac sodium respectively. Conclusion:The method is accurate and the network performs satisfactorily, and the method could be used as reference for determining drugs which UV spectrum are overlapped.

关 键 词：氯芬待因 可待因 磷酸 双氯芬酸钠 人工神经网络 含量测定 

分 类 号：R927.2[医药卫生—药学] R971.1