基于自组织竞争型神经网络的化橘红指纹图谱研究  

Research of Exocarpium Citri Grandis Fingerprint Based on Self-organization Competitive Neural Network

作　　者：陈南迪[1] 卢丽萍[1] 汪金玉[1] 林励[1] 

机构地区：[1]广州中医药大学中药学院,广州510006

出　　处：《中药新药与临床药理》2012年第5期562-566,共5页Traditional Chinese Drug Research and Clinical Pharmacology

基　　金：国家科技部十二五国家科技支撑计划(2011BAI01B02)

摘　　要：目的建立不同品种化橘红指纹图谱的自组织竞争型人工神经网络判别方法。方法采用傅里叶红外光谱法及HPLC法建立不同品种化橘红的指纹图谱,采用自组织竞争型人工神经网络进行模式识别。结果自组织竞争型神经网络模型对化橘红粉末、提取物红外及HPLC指纹图谱预测平均准确率达91.67%以上。结论自组织竞争型人工神经网络可有效用于化橘红品种的识别。Objective To establish the self-organization competitive neural network method for identifying the species by the fingerprints of different kinds of Exocarpium Citri Grandis （Cirrus grandis Peel）. Methods The fingerprints of different species of Exocarpium Citri Grandis were established by fourier transform infrared spectroscopy and high performance liquid chromatogram （HPLC）. And then we used the self-organization competitive neural network model to distinguish the different species of Exocarpium Citri Grandis. Results The self-organization competitive neural net- work for distinguish Exocarpium Citri Grandis of different species was established, and the rate of accuracy for infrared and HPLC fingerprint of the powder and the extract was more than 91.67 % in average. Conclusion The self-organizing competitiveneural network can he used for distinguishing different species of Exocarpium Citri Grandis by their fingerprints.

关 键 词：化橘红 自组织竞争神经网络 品种鉴别 红外指纹图谱 HPLC指纹图谱 

分 类 号：R284.1[医药卫生—中药学]