Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/1467
Full metadata record
DC FieldValueLanguage
dc.contributor.authorAcar, Erdem-
dc.date.accessioned2019-06-26T08:07:00Z
dc.date.available2019-06-26T08:07:00Z
dc.date.issued2015-03-04
dc.identifier.citationAcar, E. (2015). Increasing automobile crash response metamodel accuracy through adjusted cross validation error based on outlier analysis. International journal of crashworthiness, 20(2), 107-122.en_US
dc.identifier.issn1358-8265
dc.identifier.urihttps://doi.org/10.1080/13588265.2014.977839-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/1467-
dc.description.abstractAutomakers spread on effort to maintain the crashworthiness of vehicle structures while aiming to reduce their weight. Substantial weight savings can be obtained by vehicle redesign through optimisation. Finite element based crashworthiness simulation models have contributed greatly to the optimisation of vehicle structures. These high-fidelity crash simulations may be performed many times during optimisation, thereby making optimisation studies computationally intractable. Metamodels (surrogate models) that can mimic the behaviour of the crash simulation models emerge as a solution to the computational burden. Prediction capability in metamodelling can be improved by combining many different metamodels in the form of an ensemble model. In this paper, approaches based on outlier analysis of cross validation errors are proposed to increase the accuracy of ensemble models constructed for crash response predictions. Full frontal and offset frontal crash response predictions of a c-class passenger car is used for demonstration, and it is found that the proposed approach reduces the metamodelling errors up to 12% and on average by about 4.5%.en_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofInternational Journal Of Crashworthinessen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectoutlieren_US
dc.subjectmetamodelen_US
dc.subjectautomobileen_US
dc.subjectsurrogate modelen_US
dc.subjectcross validationen_US
dc.subjectcrashen_US
dc.titleIncreasing automobile crash response metamodel accuracy through adjusted cross validation error based on outlier analysisen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Mechanical Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Makine Mühendisliği Bölümütr_TR
dc.identifier.volume20
dc.identifier.issue2
dc.identifier.startpage107
dc.identifier.endpage122
dc.authorid0000-0002-3661-5563-
dc.identifier.wosWOS:000348512600001en_US
dc.identifier.scopus2-s2.0-84921602502en_US
dc.institutionauthorAcar, Erdem-
dc.identifier.doi10.1080/13588265.2014.977839-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.dept02.7. Department of Mechanical Engineering-
Appears in Collections:Makine Mühendisliği Bölümü / Department of Mechanical Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

3
checked on Mar 23, 2024

WEB OF SCIENCETM
Citations

6
checked on Mar 23, 2024

Page view(s)

54
checked on Mar 25, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.