Sea level forecasting using deep recurrent neural networks with high-resolution hydrodynamic model
author
Rajabi Kiasari, Saeed
Ellmann, Artu
Delpeche-Ellmann, Nicole Camille
statement of authorship
Saeed Rajabi-Kiasari, Artu Ellmann, Nicole Delpeche-Ellmann
source
Applied ocean research
publisher
Elsevier
journal volume number month
vol. 157
year of publication
2025
pages
art. 104496, 25 p. : ill
url
https://doi.org/10.1016/j.apor.2025.104496
subject term
meretase
hüdrogeoloogia
sügavõpe
tehisnärvivõrgud
mälu
ilmaennustused
subject of location
Läänemeri
Soome laht
keyword
sea level forecasting
LSTM
Long Short-Term Memory Networks (LSTMs)
GRU
Gated Recurrent Unit (GRU)
Baltic Sea
deep learning (DL)
recurrent neural networks (RNN)
spatiotemporal prediction
Gulf of Finland
hydro-geodesy
ISSN
0141-1187
1879-1549
notes
Bibliogr.: 98 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
1.1
Scopus
https://www.scopus.com/sourceid/26776
https://www.scopus.com/pages/publications/86000312700?origin=resultslist
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=APPL%20OCEAN%20RES&year=2024
https://www.webofscience.com/wos/woscc/full-record/WOS:001444867300001
category (general)
Engineering
Tehnika
category (sub)
Engineering. Ocean engineering
Tehnika. Ookeani tehnika
TalTech department
ehituse ja arhitektuuri instituut
küberneetika instituut
Department of Civil Engineering and Architecture
Department of Cybernetics
language
English
Inglise