1. University of Kragujevac Digital Archive
  2. University of Kragujevac
  3. Faculty of Engineering, Kragujevac
Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/23069
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dc.contributor.authorIvković, Djordje-
dc.contributor.authorArsić, Dušan-
dc.contributor.authorAdamovic, Dragan-
dc.contributor.authorSedmak, Aleksandar-
dc.contributor.authorDelić, Marko-
dc.contributor.authorVulovic, Radun-
dc.contributor.editorZhang, Zhiliang-
dc.date.accessioned2026-03-03T09:05:40Z-
dc.date.available2026-03-03T09:05:40Z-
dc.date.issued2026-
dc.identifier.issn0013-7944en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/23069-
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.relation.ispartofEngineering Fracture Mechanicsen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.titleA new artificial neural network model for prediction of fatigue strength and yield strength of various steel gradesen_US
dc.typearticleen_US
dc.description.versionPublisheden_US
dc.identifier.doi10.1016/j.engfracmech.2026.111990en_US
dc.type.versionPublishedVersionen_US
dc.source.conferenceECF 24, Zagreb 2024en_US
Appears in Collections:Faculty of Engineering, Kragujevac

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