an:06540753
Zbl 1338.86015
Moussa, H.; Benallal, M. A.; Goyet, C.; Lef??vre, N.; El Jai, M. C.; Guglielmi, V.; Touratier, F.
A comparison of multiple non-linear regression and neural network techniques for sea surface salinity estimation in the tropical Atlantic Ocean based on satellite data
EN
ESAIM, Proc. Surv. 49, 65-77 (2015).
00352630
2015
j
86A32 86A05
Summary: Using measurements of Sea Surface Salinity and Sea Surface Temperature in the Western Tropical Atlantic Ocean, from 2003 to 2007 and 2009, we compare two approaches for estimating Sea Surface Salinity : Multiple Non-linear Regression and Multi Layer Perceptron. In the first experiment, we use 18,300 \textit{in situ} data points to establish the two models, and 503 points for testing their \textit{extrapolation}. In the second experiment, we use 15,668 \textit{in situ} measurements for establishing the models, and 3,232 data points to test their \textit{interpolation}. The results show that the Multiple Non-linear Regression is an admissible solution whether it be \textit{interpolation} or \textit{extrapolation}. Yet, the Multi Layer Perceptron can be used only for \textit{interpolation}.