Prediction of behavior of fresh concrete exposed to vibration using artificial neural networks and regression model

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dc.contributor.authorAktas, Gultekin
dc.contributor.authorOzerdem, Mehmet Sirac
dc.date.accessioned2024-04-24T17:15:16Z
dc.date.available2024-04-24T17:15:16Z
dc.date.issued2016
dc.departmentDicle Üniversitesien_US
dc.description.abstractThis paper aims to develop models to accurately predict the behavior of fresh concrete exposed to vibration using artificial neural networks (ANNs) model and regression model (RM). For this purpose, behavior of a full scale precast concrete mold was investigated experimentally and numerically. Experiment was performed under vibration with the use of a computer-based data acquisition system. Transducers were used to measure time-dependent lateral displacements at some points on mold while both mold is empty and full of fresh concrete. Modeling of empty and full mold was made using both ANNs and RM. For the modeling of ANNs: Experimental data were divided randomly into two parts. One of them was used for training of the ANNs and the remaining part was used for testing the ANNs. For the modeling of RM: Sinusoidal regression model equation was determined and the predicted data was compared with measured data. Finally, both models were compared with each other. The comparisons of both models show that the measured and testing results are compatible. Regression analysis is a traditional method that can be used for modeling with simple methods. However, this study also showed that ANN modeling can be used as an alternative method for behavior of fresh concrete exposed to vibration in precast concrete structures.en_US
dc.identifier.doi10.12989/sem.2016.60.4.655
dc.identifier.endpage665en_US
dc.identifier.issn1225-4568
dc.identifier.issn1598-6217
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-84992735485
dc.identifier.scopusqualityQ2
dc.identifier.startpage655en_US
dc.identifier.urihttps://doi.org/10.12989/sem.2016.60.4.655
dc.identifier.urihttps://hdl.handle.net/11468/18395
dc.identifier.volume60en_US
dc.identifier.wosWOS:000387157600006
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherTechno-Pressen_US
dc.relation.ispartofStructural Engineering and Mechanics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPrecast Concrete Molden_US
dc.subjectCompaction Of Fresh Concreteen_US
dc.subjectVibrationen_US
dc.subjectModelingen_US
dc.subjectArtificial Neural Networks (Anns)en_US
dc.subjectRegression Modelen_US
dc.titlePrediction of behavior of fresh concrete exposed to vibration using artificial neural networks and regression modelen_US
dc.titlePrediction of behavior of fresh concrete exposed to vibration using artificial neural networks and regression model
dc.typeArticleen_US

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