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dc.contributor.authorAkkurt, Sedat
dc.contributor.authorÖzdemir, Serhan
dc.contributor.authorTayfur, Gökmen
dc.contributor.authorAkyol, Burak
dc.date.accessioned2016-05-30T12:08:44Z
dc.date.available2016-05-30T12:08:44Z
dc.date.issued2003-07
dc.identifier.citationAkkurt, S., Özdemir, S., Tayfur, G., and Akyol, B. (2003). The use of GA-ANNs in the modelling of compressive strength of cement mortar. Cement and Concrete Research, 33(7), 973-979. doi:10.1016/S0008-8846(03)00006-1en_US
dc.identifier.issn0008-8846
dc.identifier.urihttp://doi.org/10.1016/S0008-8846(03)00006-1
dc.identifier.urihttp://hdl.handle.net/11147/4684
dc.description.abstractIn this paper, results of a project aimed at modelling the compressive strength of cement mortar under standard curing conditions are reported. Plant data were collected for 6 months for the chemical and physical properties of the cement that were used in model construction and testing. The training and testing data were separated from the complete original data set by the use of genetic algorithms (GAs). A GA-artificial neural network (ANN) model based on the training data of the cement strength was created. Testing of the model was also done within low average error levels (2.24%). The model was subjected to sensitivity analysis to predict the response of the system to different values of the factors affecting the strength. The plots obtained after sensitivity analysis indicated that increasing the amount of C3S, SO3 and surface area led to increased strength within the limits of the model. C2S decreased the strength whereas C3A decreased or increased the strength depending on the SO3 level. Because of the limited data range used for training, the prediction results were good only within the same range. The utility of the model is in the potential ability to control processing parameters to yield the desired strength levels and in providing information regarding the most favourable experimental conditions to obtain maximum compressive strength.en_US
dc.description.sponsorshipIzmir Institute of Technology and Çimentaş Cement Companyen_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.isversionof10.1016/S0008-8846(03)00006-1en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectArtificial neural networksen_US
dc.subjectPortland cementen_US
dc.subjectData setsen_US
dc.subjectCompressive strengthen_US
dc.subjectGenetic algorithmsen_US
dc.titleThe use of GA-ANNs in the modelling of compressive strength of cement mortaren_US
dc.typearticleen_US
dc.contributor.authorIDTR3591en_US
dc.contributor.authorIDTR130950en_US
dc.contributor.authorIDTR2054en_US
dc.contributor.institutionauthorAkkurt, Sedat
dc.contributor.institutionauthorÖzdemir, Serhan
dc.contributor.institutionauthorTayfur, Gökmen
dc.relation.journalCement and Concrete Researchen_US
dc.contributor.departmentIzmir Institute of Technology. Mechanical Engineeringen_US
dc.contributor.departmentIzmir Institute of Technology. Civil Engineeringen_US
dc.identifier.volume33en_US
dc.identifier.issue7en_US
dc.identifier.startpage973en_US
dc.identifier.endpage979en_US
dc.identifier.wosWOS:000183190600005
dc.identifier.scopusSCOPUS:2-s2.0-0037799569
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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