Laser & Optoelectronics Progress, Volume. 58, Issue 3, 3300061(2021)
Identification of X-Ray Fluorescent Spectral Paper Ashes Based on Support Vector Machine Algorithm
To analyze the main components of paper ashes and distinguish paper types, the experiment mentioned in this study prepared 30 brands of paper into paper ashes, using an X-ray fluorescent spectrometer to measure its main components. Using measurement data trained by support vector machine (SVM) classifier, the paper type and brand source were determined. The experiments accurately determined the main component data of 90 sets of paper ashes, and randomly and proportionally generated training and test sets. Using the MATLAB experimental platform, the best parameters c and g of radial-base core functions were determined by interactive testing method, and a support vector machine classification model was established. The reasons for the model misjudgment were analyzed using Pearson correlation coefficients. This study shows that an SVM classification model can effectively achieve sample classification, can be used to test the type of paper ashes and brand source, is beneficial to solve the court-science-related problems, and can provide assistance for police to collect physical evidence at a crime scene.
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Li Chunyu, Liu Jinkun, Jiang Hong, Xu Lele, Man Ji. Identification of X-Ray Fluorescent Spectral Paper Ashes Based on Support Vector Machine Algorithm[J]. Laser & Optoelectronics Progress, 2021, 58(3): 3300061
Category: Spectroscopy
Received: May. 6, 2020
Accepted: --
Published Online: Mar. 12, 2021
The Author Email: Hong Jiang (jiangh2001@163.com)