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2012 | OriginalPaper | Chapter
The Type Detection of Mineral Oil Fluorescence Spectroscopy in Water Based on the KPCA and CCA-SVM
Authors : JiangTao Lv, QiongChan Gu
Published in: Advances in Future Computer and Control Systems
Publisher: Springer Berlin Heidelberg
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The composition of the mineral oil is complex. Especially mineral oil of 3D fluorescence spectra data dimension higher, more complex processing. In this paper, The method of kernel principal component analysis plus canonical correlation analysis (CCA) is used to do classify the spectroscopy data processed by the KPCA. Kernel method is used within principal component analysis, since CCA uses all the kernel principal component of the converted samples from KPCA, no discrimination is lost in the analysis.The experiment results show that it is effective to extract the main feature of the spectroscopy. The identification of the oils can be realized with high discrimination which is 94.11%.