Comparative Study of Several Pattern Recognition Methods in the Identification of Volatile Oils of Tradition-al Chinese Medicine by Infrared Spectroscopy / 中国药房
China Pharmacy
;
(12): 2986-2988, 2015.
Article
Dans Chinois
| WPRIM
| ID: wpr-500800
ABSTRACT
OBJECTIVE:
To compare the performance of several pattern recognition methods in the identification of volatile oils of traditional Chinese medicine(TCM)by infrared spectroscopy.METHODS:
The volatile oils of several Lonicera and Citrus TCM were determined by infrared spectroscopy. All samples of infrared spectrum were classified by hierarchical clustering,K-mean clustering,artificial neural networks,and support vector machine.RESULTS:
The results of hierarchical clustering and K-mean clus-tering were ineffective. Methods of artificial neural networks and support vector machine achieved correct classification rate of 100%.CONCLUSIONS:
Artificial neural networks and support vector machine can be combined with infrared spectroscopy to cre-ate chemometric fingerprinting for the identification of volatile oils of TCM.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Type d'étude:
Etude diagnostique
langue:
Chinois
Texte intégral:
China Pharmacy
Année:
2015
Type:
Article
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