A Comparison of Three Learning Methods to Predict N2O Fluxes and N Leaching
The environmental costs of intensive farming activities are
often under-estimated or not included into the rural development plans,
even though they play an important role in addressing future society¿s
needs. This paper focus on the use of statistical learning methods to
predict the N2O emissions and N leaching under several conservative scenarios,
in order to provide an alternative approach to deterministic models
at macro-scale. To that aim, three learning methods, namely neural networks
(multilayer perceptrons), SVM and random forests, are compared
and provide accurate solutions.
VILLA VIALANEIX Nathalie;
FOLLADOR Marco;
LEIP Adrian;
2010-07-22
Multiprint Oy, Espoo, Finland
JRC59322
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