Evapotranspiration evaluation models based on machine learning algorithms—A comparative study

•Three evapotranspiration models have been compared, differing in input variables.•Four variants of each model were applied, varying the machine learning algorithm.•M5P Regression Tree, Bagging, Random Forest and Support Vector Regression were used.•Data refers to an experimental site in Central Flo...

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Veröffentlicht in:	Agricultural water management Jg. 217; S. 303 - 315
1. Verfasser:	Granata, Francesco
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 20.05.2019
Schlagworte:	Actual evapotranspiration algorithms artificial intelligence drought Ensemble methods evapotranspiration Florida Irrigation Machine learning prediction regression analysis Regression tree relative humidity sensible heat flux soil solar radiation Support vector regression temperature time series analysis water content water management wind speed Florida Irrigation Support vector regression Regression tree Actual evapotranspiration Ensemble methods Machine learning
ISSN:	0378-3774, 1873-2283
Online-Zugang:	Volltext
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