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Laser-induced breakdown spectroscopy applied to the characterization of rock by support vector machine combined with principal component analysis

查看全文 作　　者：[1]杨洪星;[1,2]付洪波;[1,2]王华东;[1,2]贾军伟;Markus W [3]Sigrist;[1,2]董凤忠 高影响力作者 机构地区：[1]Anhui Provincial Key Laboratory of Photonic Devices and Materials, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China;[2]University of Science and Technology of China, Hefei 230026, China;[3]ETH Zurich, Institute for Quantum Electronics, Otto-Stern- Weg 1, CH-8093 Zurich, Switzerland高影响力机构 出　　处：《Chinese Physics B》索引2016年第25卷第6期,共6页高影响力期刊 基　　金：Project supported by the National Natural Science Foundation of China(Grant No.11075184);the Knowledge Innovation Program of the Chinese Academy of Sciences(CAS)(Grant No.Y03RC21124);the CAS President’s International Fellowship Initiative Foundation(Grant No.2015VMA007) 摘　　要：Laser-induced breakdown spectroscopy(LIBS) is a versatile tool for both qualitative and quantitative analysis.In this paper,LIBS combined with principal component analysis(PCA) and support vector machine(SVM) is applied to rock analysis.Fourteen emission lines including Fe,Mg,Ca,Al,Si,and Ti are selected as analysis lines.A good accuracy(91.38% for the real rock) is achieved by using SVM to analyze the spectroscopic peak area data which are processed by PCA.It can not only reduce the noise and dimensionality which contributes to improving the efficiency of the program,but also solve the problem of linear inseparability by combining PCA and SVM.By this method,the ability of LIBS to classify rock is validated. 关 键 词：主成分分析 支持向量机 岩石特征 光谱技术 激光诱导 应用 击穿 SVM
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