Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/1686
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dc.contributor.authorKilic, Gokhan-
dc.contributor.authorUnluturk, Mehmet S.-
dc.date.accessioned2023-06-16T14:19:09Z-
dc.date.available2023-06-16T14:19:09Z-
dc.date.issued2014-
dc.identifier.issn1058-9759-
dc.identifier.issn1477-2671-
dc.identifier.urihttps://doi.org/10.1080/10589759.2014.941839-
dc.identifier.urihttps://hdl.handle.net/20.500.14365/1686-
dc.description.abstractGround penetrating radar (GPR) is a highly researched area; however, despite this, there is a lack of knowledge about the well-known problem of moisture distorting the results of GPR surveys. This research analyses the results of a GPR survey on a Case Study Bridge structure in order to analyse this effect, specifically when checking for the positioning of rebar. The expected distortions of the GPR results due to the presence of moisture were indeed present, as further evidenced by subsequent destructive testing and velocity analysis. Furthermore, neural networks were also utilised to detect moisture ingress from the GPR raw data.en_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofNondestructıve Testıng And Evaluatıonen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGPR and data processingen_US
dc.subjectbridge structuresen_US
dc.subjectnon-destructiveen_US
dc.subjectmoisture ingressen_US
dc.subjectneural networksen_US
dc.subjectback-propagation learning algorithmen_US
dc.subjectNdt Methodsen_US
dc.subjectConcreteen_US
dc.subjectVariabilityen_US
dc.titlePerformance evaluation of the neural networks for moisture detection using GPRen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/10589759.2014.941839-
dc.identifier.scopus2-s2.0-84907591215en_US
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authoridKILIC, GOKHAN/0000-0001-6928-226X-
dc.authorscopusid40761843000-
dc.authorscopusid6508114835-
dc.identifier.volume29en_US
dc.identifier.issue4en_US
dc.identifier.startpage283en_US
dc.identifier.endpage296en_US
dc.identifier.wosWOS:000342322500002en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
dc.identifier.wosqualityQ2-
item.grantfulltextreserved-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.openairetypeArticle-
item.fulltextWith Fulltext-
item.languageiso639-1en-
crisitem.author.dept05.03. Civil Engineering-
crisitem.author.dept05.04. Software Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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