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Advances in Future Computer and Control Systems pp 19–22Cite as

The Type Detection of Mineral Oil Fluorescence Spectroscopy in Water Based on the KPCA and CCA-SVM

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 160))

Abstract

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%.

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References

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Author information

Authors and Affiliations

  1. Department of Automation Engineering, Northeastern University at Qinhuangdao, 066004, Qinhuangdao, China

    JiangTao Lv & QiongChan Gu

Authors
  1. JiangTao Lv
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  2. QiongChan Gu
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Corresponding author

Correspondence to JiangTao Lv .

Editor information

Editors and Affiliations

  1. Researcher Association, Wuhan Section, International Science & Education, Special No.1, Jiangxia Road of Wuhan, Wuhan, China, People's Republic

    David Jin

  2. Researcher Association, Guangzhou Section, International Science & Education, Jinheng Road, Jinbi Garden 85-1102 144, Guang Zhou, China, People's Republic

    Sally Lin

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© 2012 Springer-Verlag GmbH Berlin Heidelberg

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Cite this paper

Lv, J., Gu, Q. (2012). The Type Detection of Mineral Oil Fluorescence Spectroscopy in Water Based on the KPCA and CCA-SVM. In: Jin, D., Lin, S. (eds) Advances in Future Computer and Control Systems. Advances in Intelligent and Soft Computing, vol 160. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29390-0_4

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  • DOI: https://doi.org/10.1007/978-3-642-29390-0_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29389-4

  • Online ISBN: 978-3-642-29390-0

  • eBook Packages: EngineeringEngineering (R0)

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