Methods The HPLC data from 29 samples with different quality were proceeded with nonlinear kernel principal component analysis(KPCA) and an improved Back propagation algorithm of ANN.
方法首先通过实验获取同一品种不同质量29个白芍样本的高效液相色谱数据,然后依照非线性[的]核主成分分析(KP-CA)进行数学特征提取,将取得的压缩数据,输入BP神经网络进行学习,运用训练后的网络识别白芍的质量分类。