【摘要】 用红外光谱仪测量了VC银翘片的近红外谱图,然后将主成分分析法(PCA)和线性神经网络结合,分析VC银翘片中的对乙酰氨基酚和维生素C的含量。讨论了主成分数的选择及影响神经网络的各参数。为了比较算法的性能,作者又分别采用了偏最小二乘法、主成分分析结合BP神经网络进行数据处理。实验及数据处理结果表明,在3种多组分分析方法中,主成分分析结合线性神经网络的方法具有最高的预测精度。更多还原

【Abstract】 We measured NIR spectrum of VC Yinqiao tablets with spectral instrument, analy zed the contents of acetaminophen and vitamin C in the VC Yinqiao tablets with principal component analysis(PCA) and Linear Neural Network, and discussed the c hoice of principal component number and ANN’s parameters affecting the network . To compare arithmetic performance, the authors also processed the spectral data with p artial least squares and PCA-BP neural network. Compared with other two data pr ocess methods, the experiment and the result of data process showed that the PCA -linear neural network possess the best forecasting precision.更多还原