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Ocean Science An interactive open-access journal of the European Geosciences Union

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Ocean Sci., 13, 303-313, 2017
http://www.ocean-sci.net/13/303/2017/
doi:10.5194/os-13-303-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Technical note
19 Apr 2017
Technical note: Evaluation of three machine learning models for surface ocean CO2 mapping
Jiye Zeng et al.

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Short summary
Three machine learning models were investigated for the reconstruction of global surface ocean CO2 concentration. They include self-organizing maps (SOMs), feedforward neural networks (FNNs), and support vector machines (SVMs). Our results show that the SVM performs the best, the FNN the second, and the SOM the worst. While the SOM does not have over-fitting problems, it is sensitive to data scaling and its discrete interpolation may not be good for some applications.
Three machine learning models were investigated for the reconstruction of global surface ocean...
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