Least-squares support vector machines modelization for time-resolved spectroscopy |
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Authors: | Chauchard Fabien Roussel Sylvie Roger Jean-Michel Bellon-Maurel Véronique Abrahamsson Christoffer Svensson Tomas Andersson-Engels Stefan Svanberg Sune |
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Affiliation: | Information and Technologies for Agro-processes Cemagref, BP 5095, 34033 Montpellier, Cedex 1, France. fabien.chauchard@montpellier.cemagref.fr |
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Abstract: | By use of time-resolved spectroscopy it is possible to separate light scattering effects from chemical absorption effects in samples. In the study of propagation of short light pulses in turbid samples the reduced scattering coefficient and the absorption coefficient are usually obtained by fitting diffusion or Monte Carlo models to the measured data by use of numerical optimization techniques. In this study we propose a prediction model obtained with a semiparametric modeling technique: the least-squares support vector machines. The main advantage of this technique is that it uses theoretical time dispersion curves during the calibration step. Predictions can then be performed by use of data measured on different kinds of sample, such as apples. |
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