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Prediction of Daily Ambient Temperature and Its Hourly Estimation Using Artificial Neural Networks in an Agrometeorological Station in Castile and León, Spain

This study evaluates the predictive modeling of the daily ambient temperature (maximum, T<sub>max</sub>; average, T<sub>ave</sub>; and minimum, T<sub>min</sub>) and its hourly estimation (T<sub>0h</sub>, …, T<sub>23h</sub>) using artificial neural networks (ANNs) for agricultural applications. The d...

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Autores principales: Francisco J. Diez, Adriana Correa-Guimaraes, Leticia Chico-Santamarta, Andrés Martínez-Rodríguez, Diana A. Murcia-Velasco, Renato Andara, Luis M. Navas-Gracia
Formato: Artigo
Lenguaje:Inglês
Publicado: MDPI AG 2022-06-01
Colección:Sensors
Materias:
ambient temperature
evapotranspiration
agrometeorology
artificial neural networks (ANNs)
precision agriculture
prediction
Acceso en línea:https://www.mdpi.com/1424-8220/22/13/4850
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