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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Veröffentlicht in:	Frontiers in artificial intelligence Jg. 5; S. 963781
Hauptverfasser:	Talsma, Carl J., Solander, Kurt C., Mudunuru, Maruti K., Crawford, Brandon, Powell, Michelle R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Media S.A 12.01.2023
Schlagworte:	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
Online-Zugang:	Volltext
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