Convolutional autoencoder latent-space modeling with climate-index–conditioned recurrent networks for assessing subseasonal potential forecast skill of the Baltic Sea heat content
author
Hayatijozani, Ali
Barzandeh, Amirhossein
Maljutenko, Ilja
Raudsepp, Urmas
statement of authorship
Ali Hayatijozani, Amirhossein Barzandeh, Ilja Maljutenko, Urmas Raudsepp
source
Engineering applications of artificial intelligence
publisher
Elsevier
journal volume number month
vol. 176, 2
year of publication
2026
pages
art. 114807
url
https://doi.org/10.1016/j.engappai.2026.114807
subject term
sügavõpe
tehisnärvivõrgud
ilmaennustused
prognostika
merevesi
soojus
subject of location
Läänemeri
keyword
deep learning (DL)
convolutional autoencoder
recurrent neural networks (RNNs)
subseasonal forecasting
ocean heat content
Baltic Sea
ISSN
0952-1976
1873-6769
scientific publication
teaduspublikatsioon
classifier
1.1
TalTech department
meresüsteemide instituut
Department of Marine Systems
language
English
Inglise