Soil water erosion susceptibility assessment using deep learning algorithms

•Soil water erosion (SWE) is predicted though three kinds of deep learning algorithms.•Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Long-Short Term Memory (LSTM) are investigated.•All three models had good prediction performance, with RNN being marginally the most superior....

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Vydané v:	Journal of hydrology (Amsterdam) Ročník 618; s. 129229
Hlavní autori:	Khosravi, Khabat, Rezaie, Fatemeh, Cooper, James R., Kalantari, Zahra, Abolfathi, Soroush, Hatamiafkoueieh, Javad
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.03.2023
Predmet:	CNN Deep learning ecosystems erosion control infrastructure Land degradation LSTM neural networks prediction RNN Soil erosion soil water water erosion water quality watersheds Deep learning CNN Soil erosion RNN LSTM Land degradation
ISSN:	0022-1694, 1879-2707, 1879-2707
On-line prístup:	Získať plný text
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