RSST-ARGM: a data-driven approach to long-term sea surface temperature prediction
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1687-1499
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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online resource.
- Erschienen in
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RSST-ARGM: a data-driven approach to long-term sea surface temperature prediction ; volume:2021 ; number:1 ; day:26 ; month:8 ; year:2021 ; pages:1-18 ; date:12.2021
EURASIP journal on wireless communications and networking / European Association for Speech, Signal and Image Processing ; 2021, Heft 1 (26.8.2021), 1-18, 12.2021
- Urheber
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Zhu, Linqian
Liu, Qi
Liu, Xiaodong
Zhang, Yonghong
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s13638-021-02044-9
- URN
-
urn:nbn:de:101:1-2021111120112999707793
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:35 MESZ
Datenpartner
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Beteiligte
- Zhu, Linqian
- Liu, Qi
- Liu, Xiaodong
- Zhang, Yonghong
- SpringerLink (Online service)
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