Application and MATLAB realization of drugs' classification based on the combination of NIRS detection and BP ANN algorithm
10.3760/cma.j.issn.1673-4181.2016.04.007
- VernacularTitle:近红外光谱检测结合BP神经网络用于药物分类及MATLAB实现
- Author:
Yunfang JIA
;
Changmin MIN
;
Cheng JU
;
Bo ZHU
;
Peng WANG
- Publication Type:Journal Article
- Keywords:
Near infra-red spectrum;
Error back propagation;
Artificial neural network;
Principal components analysis;
MATLAB
- From:
International Journal of Biomedical Engineering
2016;39(4):222-225,后插12
- CountryChina
- Language:Chinese
-
Abstract:
Objective To realize rapid and non-destructive drug classification and improve the accuracy of drug classification.Methods A model for drug classification based on the combination of principal components analysis and artificial neural network (PCA-ANN) method was introduced.The software for drugs classification was then developed with the utility of MATLAB language.The near infra-red spectrum (NIRS) detection technique was executed on five kinds of drugs (a total of 120 batch samples) and the detection data was collected within the range of 1 350-1 800 nm of excitation wavelength and 0.5 nm of wavelength interval.Results The network training mean square error (MSE) was 5.91e-03,and the prediction error (β) was 2.469％ when the number of the interfering drugs number was less than 5.Conclusions The classification of drugs by NIRS combined with PCA-ANN is feasible and the classification accuracy can be increased.
