guest ::
Neural networks for improving wind power efficiency: a review
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In
Special Issue "Wind and Wave Renewable Energy Systems, Volume II" / Special Issue Editors: Ioannis K. Chatjigeorgiou, Guest Editor; Dimitrios N. Konispoliatis, Guest Editor
In
Fluids 7(12), Seiten/Artikel-Nr.:367
2022
Online
DOI: 10.3390/fluids7120367
DOI: 10.18154/RWTH-2023-00754
URL: https://publications.rwth-aachen.de/record/888703/files/888703.pdf
Einrichtungen
- Lehrstuhl für Strömungslehre und Aerodynamisches Institut (415110)
- Aachen Institute for Advanced Study in Computational Engineering Science (080003)
Thematische Einordnung (Klassifikation)
DDC: 530
OpenAccess: 
PDF
Dokumenttyp
Journal Article (Review Article)/Contribution to a book
Format
online
Sprache
English
Anmerkung
Peer reviewed article
Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85144676681
WOS Core Collection: WOS:000902649500001
Interne Identnummern
RWTH-2023-00754
Datensatz-ID: 888703
Beteiligte Länder
Germany, South Korea
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; Article Processing Charges ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Emerging Sources Citation Index ; Fees ; SCOPUS ; Web of Science Core Collection
PDF