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Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale
Papacharalampous, Georgia
ORCID iD:
0000-0001-5446-954X
Tyralis, Hristos
Pechlivanidis, Ilias
SMHI, Research Department, Hydrology.
ORCID iD:
0000-0002-3416-317X
Grimaldi, Salvatore
Volpi, Elena
Show others and affiliations
2022 (English)
In:
Geoscience Frontiers, ISSN 1674-9871, Vol. 13, no 3, article id 101349
Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2022. Vol. 13, no 3, article id 101349
National Category
Oceanography, Hydrology and Water Resources
Research subject
Hydrology
Identifiers
URN:
urn:nbn:se:smhi:diva-6265
DOI:
10.1016/j.gsf.2022.101349
ISI:
000788107300003
OAI: oai:DiVA.org:smhi-6265
DiVA, id:
diva2:1658511
Available from:
2022-05-16
Created:
2022-05-16
Last updated:
2022-05-16
Bibliographically approved
Open Access in DiVA
Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale
(26473 kB)
76 downloads
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617f75f062f754373d2b00177e925353ceb798e1d140d192a6dace9407702bdc2b71204e5b3966ae7338ad529aaa7d563441f5a991c247b17ee8d1da69c2fd6f
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Pechlivanidis, Ilias
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Direct link
http://smhi.diva-portal.org/smash/record.jsf?pid=diva2:1658511
Cite
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apa
ieee
modern-language-association-8th-edition
vancouver
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ieee
modern-language-association-8th-edition
vancouver
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en-GB
en-US
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nn-NB
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