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Graph Neural Networks for Prediction of Fuel Ignition Quality

; ; ; ; ;

In
Energy & fuels 34(9), Seiten/Artikel-Nr.:11395-11407

ImpressumColumbus, Ohio : American Chemical Society

ISSN1520-5029

Online
DOI: 10.1021/acs.energyfuels.0c01533


Einrichtungen

  1. Lehrstuhl für Systemverfahrenstechnik (416710)
  2. The Fuel Science Center (080066)
  3. Lehrstuhl für Informatik 7 (Logik und Theorie diskreter Systeme) (122910)
  4. Fachgruppe Informatik (120000)
  5. Aachener Verfahrenstechnik (416100)
  6. JARA-ENERGY (080011)


Thematische Einordnung (Klassifikation)
DDC: 660


Dokumenttyp
Journal Article

Format
online, print

Sprache
English

Anmerkung
Peer reviewed article

Externe Identnummern
WOS Core Collection: WOS:000574904900087
SCOPUS: SCOPUS:2-s2.0-85095432919

Interne Identnummern
RWTH-2020-09710
Datensatz-ID: 803415

Beteiligte Länder
Germany

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Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Multimedia (Video)/Conference Presentation  ;  ;  ;  ;  ;
Graph neural networks for prediction of fuel ignition quality
AIChE Annual Meeting, Applications of Data Science to Molecules and Materials Session, onlineonline, 18 Nov 2020 - 18 Nov 20202020-11-182020-11-18 Aachen, [AVT research video] [5], 1 Online-Ressource (1 video file) () [10.18154/RWTH-2020-10689]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Poster  ;  ;  ;  ;  ;  ;
Graph Neural Networks for Prediction of Fuel Ignition Quality
Fuel Science - From Production to Propulsion, Aachen onlineAachen online, Germany, 23 Jun 2020 - 25 Jun 20202020-06-232020-06-25  GO   Download fulltextHomepage of event BibTeX | EndNote: XML, Text | RIS


Medline ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Essential Science Indicators ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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The record appears in these collections:
Document types > Articles > Journal Articles
Faculty of Mathematics, Computer Science and Natural Sciences (Fac.1) > Department of Computer Science
Faculty of Mechanical Engineering (Fac.4)
Central and Other Institutions
Public records
Publications database
120000
080011
080066
416710
122910
416100

 Record created 2020-10-02, last modified 2023-03-21



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