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Title:

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

Document type:
Zeitschriftenaufsatz
Author(s):
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...     »
Keywords:
extreme indices; FNN; LSTM; rainfall downscaling; Vietnamese Mekong Delta
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Journal title:
International Journal of Climatology
Year:
2019
Journal volume:
39
Journal issue:
10
Pages contribution:
4170-4188
Covered by:
Scopus; Web of Science
Reviewed:
ja
Language:
en
Fulltext / DOI:
doi:10.1002/joc.6066
Publisher:
Wiley
E-ISSN:
1097-0088
Impact Factor:
3.601 (2018)
Date of publication:
01.04.2019
Copyright statement:
Copyright: © 2019 Royal Meteorological Society (RMetS). All rights reserved.
Format:
Text
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