
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Dahlkemper, Jörg | - |
dc.contributor.author | Sahlke, Max | - |
dc.date.accessioned | 2025-04-03T09:44:50Z | - |
dc.date.available | 2025-04-03T09:44:50Z | - |
dc.date.created | 2022-09-30 | - |
dc.date.issued | 2025-04-03 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.12738/17352 | - |
dc.description.abstract | Diese Arbeit behandelt die Entwicklung einer optimierten statistischen Versuchsplanungs Methodik zur Erstellung von surrogate Modellen. Ziel dieser Methodik ist es die durchschnittliche Wertigkeit der mittels Simulationen erstellter Datenpunkte zu erhöhen. Dies führt dazu, dass Modelle der gleichen Güte mit weniger Datenpunkten erstellt werden können oder bessere Modelle mit der gleichen Datenmenge. | de |
dc.description.abstract | This report describes the development of an optimised design of experiment methodology for the creation of surrogate models. The goal of this method is to increase the average value of the simulated data samples. This yields to the possibility to generate models with the same quality with less data, or models with better quality with the same amount of data. Hence, there is the potential to save cost and time in many development processes while increasing the overall quality. | en |
dc.language.iso | en | en_US |
dc.subject | Design of experiments | en_US |
dc.subject | adaptive sampling | en_US |
dc.subject | Luftfahrt | en_US |
dc.subject | maschinelles Lernen | en_US |
dc.subject | aviation | en_US |
dc.subject | machine learning | en_US |
dc.subject | surrogate model | en_US |
dc.subject.ddc | 600: Technik | en_US |
dc.title | Development of an optimised design of experiments methodology for the creation of surrogate models | en |
dc.type | Thesis | en_US |
openaire.rights | info:eu-repo/semantics/openAccess | en_US |
thesis.grantor.department | Fakultät Technik und Informatik | en_US |
thesis.grantor.department | Department Informations- und Elektrotechnik | en_US |
thesis.grantor.universityOrInstitution | Hochschule für Angewandte Wissenschaften Hamburg | en_US |
tuhh.contributor.referee | Garcia, Jasone Garay | - |
tuhh.identifier.urn | urn:nbn:de:gbv:18302-reposit-209932 | - |
tuhh.oai.show | true | en_US |
tuhh.publication.institute | Fakultät Technik und Informatik | en_US |
tuhh.publication.institute | Department Informations- und Elektrotechnik | en_US |
tuhh.type.opus | Masterarbeit | - |
dc.type.casrai | Supervised Student Publication | - |
dc.type.dini | masterThesis | - |
dc.type.driver | masterThesis | - |
dc.type.status | info:eu-repo/semantics/publishedVersion | en_US |
dc.type.thesis | masterThesis | en_US |
dcterms.DCMIType | Text | - |
tuhh.dnb.status | domain | en_US |
item.advisorGND | Dahlkemper, Jörg | - |
item.grantfulltext | open | - |
item.languageiso639-1 | en | - |
item.openairetype | Thesis | - |
item.openairecristype | http://purl.org/coar/resource_type/c_46ec | - |
item.fulltext | With Fulltext | - |
item.creatorGND | Sahlke, Max | - |
item.creatorOrcid | Sahlke, Max | - |
item.cerifentitytype | Publications | - |
Appears in Collections: | Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
MA_Surrogate Models.pdf | 9.82 MB | Adobe PDF | View/Open |
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