Prediction of the effect of varying cure conditions and w/c ratio on the compressive strength of concrete using artificial neural networks

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dc.contributor.authorYaprak, Hasbi
dc.contributor.authorKaraci, Abdulkadir
dc.contributor.authorDemir, Ilhami
dc.date.accessioned2020-06-25T18:07:49Z
dc.date.available2020-06-25T18:07:49Z
dc.date.issued2013
dc.departmentKırıkkale Üniversitesi
dc.descriptionKaraci, Abdulkadir/0000-0002-2430-1372; Demir, Ilhami/0000-0002-8230-4053
dc.description.abstractThe present study aims at developing an artificial neural network (ANN) to predict the compressive strength of concrete. A data set containing a total of 72 concrete samples was used in the study. The following constituted the concrete mixture parameters: two distinct w/c ratios (0.63 and 0.70), three different types of cements and three different cure conditions. Measurement of compressive strengths was performed at 3, 7, 28 and 90 days. Two different ANN models were developed, one with 4 input and 1 output layers, 9 neurons and 1 hidden layer, and the other with 5, 6 neurons, 2 hidden layers. For the training of the developed models, 60 experimental data sets obtained prior to the process were used. The 12 experimental data not used in the training stage were utilized to test ANN models. The researchers have reached the conclusion that ANN provides a good alternative to the existing compressive strength prediction methods, where different cements, ages and cure conditions were used as input parameters.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1007/s00521-011-0671-x
dc.identifier.endpage141en_US
dc.identifier.issn0941-0643
dc.identifier.issn1433-3058
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-84871969728
dc.identifier.scopusqualityQ1
dc.identifier.startpage133en_US
dc.identifier.urihttps://doi.org/10.1007/s00521-011-0671-x
dc.identifier.urihttps://hdl.handle.net/20.500.12587/5669
dc.identifier.volume22en_US
dc.identifier.wosWOS:000313062100015
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer London Ltden_US
dc.relation.ispartofNeural Computing & Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectArtificial neural networken_US
dc.subjectCementen_US
dc.subjectCompressive strengthen_US
dc.subjectCure conditionsen_US
dc.subjectAgeen_US
dc.titlePrediction of the effect of varying cure conditions and w/c ratio on the compressive strength of concrete using artificial neural networksen_US
dc.typeArticle

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