Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/32983
DC FieldValueLanguage
dc.contributor.authorMarkou, George-
dc.contributor.authorBakas, Nikolaos P.-
dc.date.accessioned2024-10-02T06:57:42Z-
dc.date.available2024-10-02T06:57:42Z-
dc.date.issued2019-
dc.identifier.citationInnovate, 2019en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14279/32983-
dc.language.isoenen_US
dc.relation.ispartofInnovateen_US
dc.titleArtificial Intelligence (A.I.) Reinforced Concrete. Algorithms predict concrete strength without training on experimental dataen_US
dc.typeOtheren_US
dc.collaborationUniversity of Pretoriaen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.subject.categoryENGINEERING AND TECHNOLOGYen_US
dc.subject.categoryCivil Engineeringen_US
dc.countryGreeceen_US
dc.countrySouth Africaen_US
dc.subject.fieldEngineering and Technologyen_US
cut.common.academicyear2019-2020en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_1843-
item.openairetypeother-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-6891-7064-
crisitem.author.parentorgFaculty of Engineering and Technology-
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