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Record link: 
http://hdl.handle.net/20.500.12708/41636
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Title: 
Data modelling approach for physical systems
en
Citation: 
Winkler, S., Körner, A., & Breitenecker, F. (2018). Data modelling approach for physical systems. In M. Affenzeller, A. Bruzzone, E. Jimenez, F. Longo, Y. Merkuryev, & M. A. Piera (Eds.), Proceedings of the 30th European Modeling and Simulation Symposium, 2018 (p. 310). DIME Università di Genova, DIMEG University of Calabria. http://hdl.handle.net/20.500.12708/41636
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Publication Type: 
Inproceedings - Full-Paper Contribution
en
Language: 
English
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Authors: 
Winkler, Stefanie 
Körner, Andreas 
Breitenecker, Felix 
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Organisational Unit: 
E101-03 - Forschungsbereich Scientific Computing and Modelling 
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Published in: 
Proceedings of the 30th European Modeling and Simulation Symposium, 2018 
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Date (published): 
Sep-2018
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Event name: 
The 30th European Modeling & Simulation Symposium, 2018 
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Event date: 
17-Sep-2018 - 19-Sep-2018
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Event place: 
Budapest, Hungary
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Number of Pages: 
310
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Publisher: 
DIME Università di Genova, DIMEG University of Calabria, 30/Rende
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Peer reviewed: 
Yes
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Abstract: 
This contribution deals with the possible applications of neural networks for hybrid models. After a basic introduction to neural networts and hybrid modelling some applications are discussed. On the one hand, the substitutability of hybrid models is up for debate. On the other hand, the possibility of combining neural networks with physical models, e. g. for determining individual parameters, are focused. In the end the discussed approaches are applied and compared using a fundamental example.
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Research Areas: 
außerhalb der gesamtuniversitären Forschungsschwerpunkte: 10%
Modelling and Simulation: 90%
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Science Branch: 
Mathematik
Sonstige Technische Wissenschaften
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Appears in Collections:
Conference Paper

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