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Comparison of clustering techniques for hybrid rocket fuel combustion data

Rüttgers, Alexander and Debus, Charlotte and Siggel, Martin and Petrarolo, Anna and Kobald, Mario (2020) Comparison of clustering techniques for hybrid rocket fuel combustion data. International Workshop on Scientific Machine Learning, 8.-10. Jan. 2020, Köln, Deutschland. (Unpublished)

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Item URL in elib:https://elib.dlr.de/133467/
Document Type:Conference or Workshop Item (Speech)
Title:Comparison of clustering techniques for hybrid rocket fuel combustion data
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Rüttgers, AlexanderAlexander.Ruettgers (at) dlr.dehttps://orcid.org/0000-0001-6347-9272
Debus, CharlotteCharlotte.Debus (at) dlr.deUNSPECIFIED
Siggel, Martinmartin.siggel (at) dlr.dehttps://orcid.org/0000-0002-3952-4659
Petrarolo, AnnaAnna.Petrarolo (at) dlr.dehttps://orcid.org/0000-0002-2291-2874
Kobald, MarioMario.Kobald (at) dlr.dehttps://orcid.org/0000-0002-1708-3944
Date:2020
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Unpublished
Keywords:clustering, rocket combustion data, hybrid rockets, machine learning
Event Title:International Workshop on Scientific Machine Learning
Event Location:Köln, Deutschland
Event Type:international Conference
Event Dates:8.-10. Jan. 2020
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Technik für Raumfahrtsysteme
DLR - Research theme (Project):R - Vorhaben SISTEC
Location: Köln-Porz
Institutes and Institutions:Institut of Simulation and Software Technology > High Performance Computing
Institut of Simulation and Software Technology
Deposited By: Rüttgers, Dr. Alexander
Deposited On:14 Jan 2020 09:36
Last Modified:14 Jan 2020 09:36

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