Abstract：In the present paper, the simultaneous determination of multi-components in Chinese herbal medicine was performed by artificial neural network-UV spectrometry. The interference of other components was eliminated by self-revising and self-simulation of the virtual component. The double ANN including training and simulation network was established, and the capabilities of self-recognition and self-studying were improved. Therefore, the prediction accuracy of multicomponent content was improved greatly in the complicated Chinese herbal medicine system. The contents of aesculin and aesculetin, which were extracted from 21 Cortex Fraxinis, were predicted. Comparing the results with those of HPLC, the prediction accuracy was more than 90% within the relative errors less than 10%. The measurement precisions of aesculin and aesculetin were 0.37% and 1.5% respectively.
白立飞，张海涛，张寒琦，王红霞，王洪艳* . 虚拟组分-人工神经网络用于中药紫外光度法中多组分的同时测定[J]. 光谱学与光谱分析, 2007, 27(01): 126-130.
BAI Li-fei, ZHANG Hai-tao, ZHANG Han-qi, WANG Hong-xia, WANG Hong-yan* . Simultaneous Determination of Multi-Components in Chinese Herbal Medicine with UV Spectrometry by Virtual Components-Artificial Neural Network . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(01): 126-130.
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