Prediction of Typhoon Track and Intensity Using a Generative Adversarial Network With Observational and Meteorological Data
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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In: 10.1109/ACCESS.2022.3172301
- Ereignis
-
Veröffentlichung
- (wo)
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Aachen
- (wer)
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Universitätsbibliothek der RWTH Aachen
- (wann)
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2022
- Urheber
- DOI
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10.18154/RWTH-2022-05400
- URN
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urn:nbn:de:101:1-2022060403492785285977
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:36 MESZ
Datenpartner
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Beteiligte
- Rüttgers, Mario
- Jeon, Soohwan
- Lee, Sangseung
- You, Donghyun
- Universitätsbibliothek der RWTH Aachen
Entstanden
- 2022
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