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drug discrimination of Near Infrared spectroscopy based on the scaled convex hull classifier

Journal of Innovative Optical Health Sciences 2014年第4期7卷 101-110页

作者： Zhenbing Liu Shujie Jiang Huihua Yang School of Electronic Engineering and AutomationGuilin University of Electronic Technology No.1 Jinji Road GuilinP.R.China

Near Infrared spectroscopy(NIRS)has been widely used in the discrimination(classification)of pharmaceutical *** real applications,however,the class imbalance of the drug samples,i.e.,the number of one drug sample may be much larger than the number of the other drugs,deceasesdrastically the discrimination performance of the classification *** address this classimbalance problem,a new computational method--the scaled convex hull(SCH)-basedmaximum margin classifier is proposed in this *** a suitable selection of the reductionfactor of the SCHs generated by the two classes of drug samples,respectively,the maximalmargin classifier bet ween SCHs can be constructed which can obtain good classification *** an optimization of the parameters involved in the modeling by Cuckoo Search,a satisfied model is achieved for the classification of the *** experiments on spectra samplesproduced by a pharmaceutical company show that the proposed method is more effective androbust than the existing ones.

关键词： drug classification Near Infrared spectroscopy class imbalance scaled convex hulls

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Deep belief network-based drug identification using near infrared spectroscopy

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Journal of Innovative Optical Health Sciences 2017年第2期10卷 1-10页

作者： Huihua Yang Baichao Hu Xipeng Pan Shengke Yan Yanchun Feng Xuebo Zhang Lihui Yin Changqin Hu College of Electronic Engineering and Automation Guilin University of Electronic Technology 1 Jinji Road Guilin 541004P.R.China A utomation School Beijing University of Posts 8 Telecommunications 10 Xitucheng Road Beijing 100876P.R.China National Institutes for Food and drug Control 10 Tiantanxili Road Beijing 100050P.R.China

Near infrared spectroscopy(NIRS)analysis technology,combined with chemometrics,can be effectively used in quick and nondestructive analysis of quality and *** this paper,an effective drug identification method by using deep belief network(DBN)with dropout mecha-nism(dropout-DBN)to model NIRS is introduced,in which dropout is employed to overcome the overfitting problem coming from the small *** paper tests proposed method under datasets of different sizes with the example of near infrared diffuse refectance spectroscopy of erythromycin ethylsuccinate drugs and other drugs,aluminum and nonaluminum ***,it gives experiments to compare the proposed method's performance with back propagation(BP)neural network,support vector machines(SVMs)and sparse denoising auto-encoder(SDAE).The results show that for both binary classification and multi-classification,dropout mechanism can improve the classification accuracy,and dropout-DBN can achieve best classification accuracy in almost all *** is similar to dropout-DBN in the aspects of classification accuracy and algorithm stability,which are higher than that of BP neural network and SVM *** terms of training time,dropout-DBN model is superior to SDAE model,but inferior to BP neural network and SVM ***,dropout-DBN can be used as a modeling tool with effective binary and multi-class classification performance on a spectrum sample set of small size.

关键词： Deep belief networks near infrared spectroscopy drug classification dropout

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