Spectroscopy and Spectral Analysis, Volume. 33, Issue 11, 3014(2013)

Application of SVR in Quantitative Analysis of Wines

LUO Tao1、*, WEI Ji-ping2, ZHAO Yu-ping3, and ZHANG Jun4
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    References(8)

    [1] [1] Gauglitz G, Vo-Dinh T. Handbook of Spectroscopy, Wiley, VCH, 2003.

    [2] [2] Griffiths P R, Haseth J. Fourier Transform Infrared Spectrometry, Wiley, 2007.

    [3] [3] Wold H. Soft Modeling by Latent Variables: the Nonlinear Literative Partial Least Squares Approach, Perspectives in Probability and Statistics, 1975.

    [4] [4] Despagne F, Massart D L. Neural Networks in Multivariate Calibration, Analyst, 1998, 123: 157R.

    [5] [5] Vapnik V. Statistical Learning Theory, Wiley, New York, 1998.

    [6] [6] Belousov A I, Verzakov S A, von Frese J. Applicational Aspects of Support Vector Machines, J. Chemom., 2002, 16: 482.

    [7] [7] Capron X, Smeyers-Verbeke J. Food Chemistry, 2007, 101(4): 1585.

    [8] [8] Ovidiu Lvanciuc. Reviews in Computational Chemistry, 2007, 23: 291.

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    LUO Tao, WEI Ji-ping, ZHAO Yu-ping, ZHANG Jun. Application of SVR in Quantitative Analysis of Wines[J]. Spectroscopy and Spectral Analysis, 2013, 33(11): 3014

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    Paper Information

    Received: Mar. 11, 2013

    Accepted: --

    Published Online: Nov. 14, 2013

    The Author Email: LUO Tao (luo_tao@tju.edu.cn)

    DOI:10.3964/j.issn.1000-0593(2013)11-3014-05

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