Generalization of Physics-Informed Neural Networks for Various Boundary and Initial Conditions

Schäfer, Violetta (2022) Generalization of Physics-Informed Neural Networks for Various Boundary and Initial Conditions. Master's, Technische Universität Kaiserslautern.

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Item URL in elib:

https://elib.dlr.de/185457/

Document Type:

Thesis (Master's)

Title:

Generalization of Physics-Informed Neural Networks for Various Boundary and Initial Conditions

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Schäfer, Violetta	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED

Date:

11 January 2022

Refereed publication:

Open Access:

Yes

Number of Pages:

Status:

Published

Keywords:

Machine Learning Neuronale Netze Partielle Differentialgleichungen

Institution:

Technische Universität Kaiserslautern

Department:

Fachbereich Mathematik

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Space

HGF - Program Themes:

Space System Technology

DLR - Research area:

Raumfahrt

DLR - Program:

R SY - Space System Technology

DLR - Research theme (Project):

R - Tasks SISTEC

Location:

Köln-Porz

Institutes and Institutions:

Institute of Software Technology > High-Performance Computing
Institute of Software Technology

Deposited By:

Schäfer, Violetta

Deposited On:

02 Mar 2022 08:40

Last Modified:

09 Mar 2022 15:28

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