Spectroscopy and Spectral Analysis, Volume. 33, Issue 11, 3014(2013)
Application of SVR in Quantitative Analysis of Wines
[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.
Get Citation
Copy Citation Text
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
Received: Mar. 11, 2013
Accepted: --
Published Online: Nov. 14, 2013
The Author Email: LUO Tao (luo_tao@tju.edu.cn)