Chinese Spirits Identification Model Based on Mid-Infrared Spectrum  

作　　者：Wu Zeng Zhanxiong Huo Yuxuan Xie Yingxiang Jiang Kun Hu 

机构地区：[1]School of Electrical and Electronic Engineering,Wuhan Polytechnic University,Wuhan,430000,China [2]Gina Cody School of Engineering and Computer Science,Concordia University,Montreal,H3G 1M8,Canada

出　　处：《Computers, Materials & Continua》2020年第9期1869-1883,共15页计算机、材料和连续体（英文）

基　　金：This work was financially supported by the National Nature Science Foundation of China(Grant Number:61962010).

摘　　要：Applying computer technology to the field of food safety,and how to identify liquor quickly and accurately,is of vital importance and has become a research focus.In this paper,sparse principal component analysis(SPCA)was applied to seek sparse factors of the mid-infrared(MIR)spectra of five famous vintage year Chinese spirits.The results showed while meeting the maximum explained variance,23 sparse principal components(PCs)were selected as features in a support vector machine(SVM)model,which obtained a 97%classification accuracy.By comparison principal component analysis(PCA)selected 10 PCs as features but only achieved an 83%classification accuracy.Although both approaches were better than a direct SVM approach based on the classification results(64%classification accuracy),they also demonstrated the importance of extracting sparse PCs,which captured most important information.The combination of computer technology SPCA and MIR provides a new and convenient method for liquor identification in food safety.

关 键 词：Mid-infrared spectra Chinese spirits SPCA SVM liquor identification 

分 类 号：R73[医药卫生—肿瘤]