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Data-driven uncertainty quantification for constrained stochastic differential equations and application to solar photovoltaic power forecast data

; ; ;

In
Statistics and computing 35(5), Seiten/Artikel-Nr.:163

ImpressumDordrecht [u.a.] : Springer Science + Business Media B.V

Umfang[1]-22

ISSN1573-1375

Online
DOI: 10.1007/s11222-025-10698-4

DOI: 10.18154/RWTH-2025-07254
URL: https://publications.rwth-aachen.de/record/1017263/files/1017263.pdf

Einrichtungen

  1. Lehrstuhl für Mathematics for Uncertainty Quantification (118110)
  2. Fachgruppe Mathematik (110000)


Thematische Einordnung (Klassifikation)
DDC: 620

OpenAccess:
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Dokumenttyp
Journal Article

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-105012541963
WOS Core Collection: WOS:001543338100001

Interne Identnummern
RWTH-2025-07254
Datensatz-ID: 1017263

Beteiligte Länder
France, Germany, Saudi Arabia, Uruguay

Lizenzstatus der Zeitschrift

 GO

Medline ; Creative Commons Attribution-NonCommercial-NoDerivs CC BY-NC-ND 4.0 ; OpenAccess ; Clarivate Analytics Master Journal List ; DEAL Springer ; Essential Science Indicators ; IF < 5 ; JCR ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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110000
118110
 Record created 2025-08-26, last modified 2025-11-06
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