Gast ::
Can energy system modeling benefit from artificial neural networks? Application of two-stage metamodels to reduce computation of security of supply assessments
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In
Next generation industrial and manufacturing technologies / edited by Xun Xu, Ray Zhong
In
Computers & industrial engineering 142, Seiten/Artikel-Nr.:106334
2020
Online
DOI: 10.18154/RWTH-2020-06050
DOI: 10.1016/j.cie.2020.106334
URL: https://publications.rwth-aachen.de/record/792355/files/792355.pdf
Einrichtungen
- Juniorprofessur für Energieressourcen- und Innovationsökonomik (816930)
- E.ON Energy Research Center (080052)
Thematische Einordnung (Klassifikation)
DDC: 004
OpenAccess: 
PDF
Dokumenttyp
Journal Article/Contribution to a book
Format
online, print
Sprache
English
Anmerkung
Peer reviewed article
Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85079000909
WOS Core Collection: WOS:000525375800018
OpenAlex: W3004246568
Interne Identnummern
RWTH-2020-06050
Datensatz-ID: 792355
Beteiligte Länder
Germany
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; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Essential Science Indicators ; IF < 5 ; IF < 5 ; JCR ; Nationallizenz
; Nationallizenz ; SCOPUS ; Science Citation Index Expanded ; Science Citation Index Expanded ; Web of Science Core Collection
PDF