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苯甲酸和水杨酸是中成药足光散的两种主要成分,使用毛细管区带电泳很难将这两种成分完全分离。寻找最优实验条件费时费力且成本高。本文应用径向基函数人工神经网络结合主成分分析处理苯甲酸和水杨酸的毛细管区带电泳重叠峰。无需对这两种酸完全分离则可准确测定足光散中两种酸的含量。测定两种酸的相对误差分别为2.662%和5.516%。这是一种简单可行的测定足光散中苯甲酸和水杨酸含量的方法。
Benzoic acid and salicylic acid are the two major components of the Chinese patent pharmacopeia. It is difficult to completely separate the two components by capillary zone electrophoresis. Finding the best experimental conditions is time-consuming and costly. In this paper, radial basis function artificial neural network combined with principal component analysis of benzoic acid and salicylic acid capillary zone electrophoresis overlap peaks. Without the need for complete separation of the two acids, it is possible to accurately determine the amount of both acids in the photoluminescence. The relative errors of the two acids were 2.662% and 5.516%, respectively. This is a simple and feasible method for the determination of benzoic acid and salicylic acid content in foot light scattering.