Frost prediction using machine learning and deep neural network models

This study describes accurate, computationally efficient models that can be implemented for practical use in predicting frost events for point-scale agricultural applications. Frost damage in agriculture is a costly burden to farmers and global food security alike. Timely prediction of frost events...

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Vydané v:	Frontiers in artificial intelligence Ročník 5; s. 963781
Hlavní autori:	Talsma, Carl J., Solander, Kurt C., Mudunuru, Maruti K., Crawford, Brandon, Powell, Michelle R.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland Frontiers Media S.A 12.01.2023
Predmet:	Artificial Intelligence earth sciences frost damage frost damage, machine learning, neural network, random forests, temperature prediction, weather models machine learning MATHEMATICS AND COMPUTING neural networks random forests temperature prediction frost damage random forests temperature prediction machine learning neural networks
ISSN:	2624-8212, 2624-8212
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