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ProLoaF : Probabilistic load forecasting for power systems

; ;

In
SoftwareX 23, Seiten/Artikel-Nr.:101487

ImpressumAmsterdam [u.a.] : Elsevier

Umfang[1]-7

ISSN2352-7110

Online
DOI: 10.1016/j.softx.2023.101487

DOI: 10.18154/RWTH-2024-00452
URL: https://publications.rwth-aachen.de/record/976928/files/976928.pdf

Einrichtungen

  1. Lehrstuhl für Automation of Complex Power Systems (616310)
  2. E.ON Energy Research Center (080052)
  3. Fraunhofer-Institut für Angewandte Informationstechnik - FIT (053300)


Thematische Einordnung (Klassifikation)
DDC: 004

OpenAccess:
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Dokumenttyp
Journal Article

Format
online

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85166977746
WOS Core Collection: WOS:001063069300001

Interne Identnummern
RWTH-2024-00452
Datensatz-ID: 976928

Beteiligte Länder
Germany

Lizenzstatus der Zeitschrift

 GO

Medline ; Creative Commons Attribution CC BY 4.0 ; DOAJ ; OpenAccess ; Article Processing Charges ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; DOAJ Seal ; Essential Science Indicators ; Fees ; IF < 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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Document types > Articles > Journal Articles
Faculty of Electrical Engineering and Information Technology (Fac.6)
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080052
616310
053300
 Record created 2024-01-14, last modified 2025-10-02
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