Show simple item record

dc.contributor.authorZafar, Muhammad Hamza
dc.contributor.authorYounis, Hassaan Bin
dc.contributor.authorMansoor, Majad
dc.contributor.authorMoosavi, Syed Kumayl Raza
dc.contributor.authorKhan, Noman Mujeeb
dc.contributor.authorAkhtar, Naureen
dc.date.accessioned2022-11-09T14:14:10Z
dc.date.available2022-11-09T14:14:10Z
dc.date.created2022-10-07T12:13:47Z
dc.date.issued2022
dc.identifier.citationZafar, M. H., Younis, H. B., Mansoor, M., Moosavi, S. K. R., Khan, N. M., & Akhtar, N. (2022). Training Deep Neural Networks with Novel Metaheuristic Algorithms for Fatigue Crack Growth Prediction in Aluminum Aircraft Alloys. Materials, 15 (18), 1-18. doi:en_US
dc.identifier.issn1996-1944
dc.identifier.urihttps://hdl.handle.net/11250/3030988
dc.language.isoengen_US
dc.publisherMDPIen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleTraining Deep Neural Networks with Novel Metaheuristic Algorithms for Fatigue Crack Growth Prediction in Aluminum Aircraft Alloysen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2022 Author(s)en_US
dc.subject.nsiVDP::Teknologi: 500en_US
dc.source.pagenumber18en_US
dc.source.volume15en_US
dc.source.journalMaterialsen_US
dc.source.issue18en_US
dc.identifier.doi10.3390/ma15186198
dc.identifier.cristin2059538
cristin.qualitycode1


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal