摘要
建立了差分拉曼光谱技术结合K-means聚类法对牙膏快速分类的方法。对37个牙膏样品编号,将其分别涂抹于载玻片上,晾干,使用差分拉曼光谱仪进行扫描。调用R语言软件中fpc、factoextra、cluster数据库中的na.omit和scale函数对37个牙膏样品的差分拉曼光谱数据进行标准化处理,利用手肘法和Gap Statistic算法优化聚类数。在最佳聚类数为4的条件下,通过K-means聚类法对牙膏样品进行分类,并使用层次聚类分析法进行验证。结果显示,37个牙膏样品被分为4类,并且两种方法的分类结果一致。
A method for rapid classification of toothpaste by differential Raman spectroscopy combined with K-means clustering method.37toothpaste samples numbered were smeared on slides and dried for scanning by differential Raman spectrometer.Functions of na.omit and scale in databases of fpc,factoextra and cluster in R language software were used to standardize the differential Raman spectral data of 37toothpaste samples,and the elbow method and Gap Statistic algorithm were used to optimize the cluster number.Under the optimal cluster number of 4,the 37toothpaste samples were classified by K-means clustering method and verified by hierarchical cluster analysis.It was showed that 37toothpaste samples were divided into 4categories,and the classification results of the two methods were consistent.
作者
孙家政
姜红
刘新磊
屈音璇
段斌
刘峰
SUN Jiazheng;JIANG Hong;LIU Xinlei;QU Yinxuan;DUAN Bin;LIU Feng(Institute of Criminal Investigation,People′s Public Security University of China,Beijing100038,China;Institute of Forensic Science,Criminal Investigation Police University of China,Shenyang110035,China;Nanjing Jianzhi Instrument and Equipment Co.,Ltd.,Nanjing210049,China)
出处
《理化检验（化学分册）》
CAS
CSCD
北大核心
2022年第1期84-89,共6页
Physical Testing and Chemical Analysis(Part B:Chemical Analysis)
基金
中央高校基本科研业务费项目(2020JKF502)
南京简智仪器设备有限公司技术合作项目(20191218)
国家重点研发计划项目(2017YFC0822004)。
