Machine Learning and Conventional Methods for Reference Evapotranspiration Estimation Using Limited-Climatic-Data Scenarios

Machine Learning and Conventional Methods for Reference Evapotranspiration Estimation Using Limited-Climatic-Data Scenarios

Reference evapotranspiration (ET<sub>0</sub>) is one important agrometeorological parameter for hydrological studies and climate risk zoning. ET<sub>0</sub> calculation by the FAO Penman–Monteith method requires several input data. However, the availability of climate data ha...

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Bibliographic Details
Main Authors: Pietros André Balbino dos Santos, Felipe Schwerz, Luiz Gonsaga de Carvalho, Victor Buono da Silva Baptista, Diego Bedin Marin, Gabriel Araújo e Silva Ferraz, Giuseppe Rossi, Leonardo Conti, Gianluca Bambi
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Agronomy
Subjects:
artificial neural network
random forest
support vector machine
multiple linear regression
crop water requirements
meteorological data
Online Access:https://www.mdpi.com/2073-4395/13/9/2366

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