Study on Detection and Classification of Liquid Foundation by SEM/EDS
In order to establish a method that combines scanning electron microscopy/energy dispersive spectrometry with multivariate statistics to detect the physical evidence of liquid foundation,the 50 liquid foundation samples collected were pretreated,analyzed and tested by SEM/EDS.The 50 samples were roughly divided into two categories.By combining K-Means clustering to process experimental data,the two major categories of samples were further divided into four categories;Finally,a classification model was constructed using the random forest algorithm,with 40 samples as the training set and 10 samples as the testing set.The prediction accuracy of the testing set reached 86.6%,and the prediction effect was good,which can achieve sample classification automation.This method is easy to operate,can achieve non-destructive testing of materials,and has good classification effects.It can be directly used for investigating and solving cases in public security organs,and has broad application prospects in the field of court science.
NETL
NSTL
万方数据
维普
