Downscaling rainfall using deep learning long short‐term memory and feedforward neural network-Reference-Cited by-同舟云学术

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

Published:2019-04 Issue:10 Volume:39 Page:4170-4188
ISSN:0899-8418
Container-title:International Journal of Climatology
language:en
Short-container-title:Int. J. Climatol

Author:

Tran Anh Duong¹²^ORCID,Van Song P.²,Dang Thanh D.³^ORCID,Hoang Long P.⁴

Affiliation:

1. Institute of Hydraulic and Water Resources EngineeringTechnical University of Munich Munich Germany

2. Environment, Water and Climate Change Adaptation research group, Vietnamese‐German University Binh Duong Vietnam

3. Pillar of Engineering Systems and DesignSingapore University of Technology and Design Tampines Singapore

4. Water Systems and Global Change GroupWageningen University Wageningen the Netherlands

Publisher

Wiley

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6066

Reference64 articles.

1. Neural networks in sedimentation modelling for the approach channel of the port area of Rotterdam

2. Contraction scour estimation using data-driven methods

3. An artificial neural network technique for downscaling GCM outputs to RCM spatial scale

4. Comparison and evaluation of multiple GCMs, statistical downscaling and hydrological models in the study of climate change impacts on runoff

5. Coupling statistical and dynamical methods for spatial downscaling of precipitation

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