Artificial neural network investigation of hardness and fracture toughness of hydroxylapatite

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dc.authoridARCAKLIOGLU, Erol/0000-0001-8073-5207
dc.authoridEvis, Zafer/0000-0002-7518-8162
dc.contributor.authorEvis, Zafer
dc.contributor.authorArcaklioglu, Erol
dc.date.accessioned2024-09-29T15:55:05Z
dc.date.available2024-09-29T15:55:05Z
dc.date.issued2011
dc.departmentKarabük Üniversitesien_US
dc.description.abstractHardness and fracture toughness of hydroxylapatite were investigated by artificial neural network (ANN). Hardness and fracture toughness of hydroxylapatite were predicted by using its sintering temperature, sintering time, relative density, and grain size with ANN. It was found that prediction results of its hardness and fracture toughness closely matched with the experimental results. (C) 2010 Elsevier Ltd and Techna Group S.r.l. All rights reserved.en_US
dc.identifier.doi10.1016/j.ceramint.2010.10.037
dc.identifier.endpage1152en_US
dc.identifier.issn0272-8842
dc.identifier.issn1873-3956
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-79952989521en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1147en_US
dc.identifier.urihttps://doi.org/10.1016/j.ceramint.2010.10.037
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4460
dc.identifier.volume37en_US
dc.identifier.wosWOS:000289383800001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Sci Ltden_US
dc.relation.ispartofCeramics Internationalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHardnessen_US
dc.subjectHydroxylapatiteen_US
dc.subjectFracture toughnessen_US
dc.subjectArtificial neural networken_US
dc.titleArtificial neural network investigation of hardness and fracture toughness of hydroxylapatiteen_US
dc.typeArticleen_US

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