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Titel:

Downscaling rainfall using deep learning long short‐term memory and feedforward neural network

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Tran Anh, Duong; Van, Song P.; Dang, Thanh D.; Hoang, Long P.
Abstract:
Choosing downscaling techniques is crucial in obtaining accurate and reliable climate change predictions, allowing for detailed impact assessments of climate change at regional and local scales. Traditional statistical methods are likely inefficient in downscaling precipitation data from multiple sources or complex data patterns, so using deep learning, a form of nonlinear models, could be a promising solution. In this study, we proposed to use deep learning models, the so-called long shor...     »
Stichworte:
extreme indices; FNN; LSTM; rainfall downscaling; Vietnamese Mekong Delta
Dewey Dezimalklassifikation:
620 Ingenieurwissenschaften
Zeitschriftentitel:
International Journal of Climatology
Jahr:
2019
Band / Volume:
39
Heft / Issue:
10
Seitenangaben Beitrag:
4170-4188
Nachgewiesen in:
Scopus; Web of Science
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1002/joc.6066
Verlag / Institution:
Wiley
E-ISSN:
1097-0088
Impact Factor:
3.601 (2018)
Publikationsdatum:
01.04.2019
Copyright Informationen:
Copyright: © 2019 Royal Meteorological Society (RMetS). All rights reserved.
Format:
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