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dc.creatorRadovanović, Slobodan
dc.creatorMilivojević, Vladimir
dc.creatorCirović, V.
dc.creatorDivac, Dejan
dc.creatorMilivojević, Nikola
dc.date.accessioned2019-04-19T14:23:19Z
dc.date.available2019-04-19T14:23:19Z
dc.date.issued2015
dc.identifier.issn1759-3433
dc.identifier.urihttp://grafar.grf.bg.ac.rs/handle/123456789/668
dc.description.abstractThe goal of this paper is to assess the effectiveness of using artificial neural networks in the prediction of concrete dam deformation. The aging of dams as a concrete structures poses a significant risk for the environment, and many of them are at the stage where it is necessary to pay attention to their behaviour. Short-term term prediction of deformation is very important for rapid response in the case of any adverse events. Two examples are presented in this paper to investigate how short-term prediction of deformation can be realized by using artificial neural networks. As a comparison, a set of statistical linear regression models are established using the same data. The conclusions on the basis of the analysis and the established models are presented. The paper provides an assessment of the network structure and a comparison of neural network models for the usual concept of statistical models for the monitoring of dams.en
dc.publisherCivil-Comp Press
dc.rightsrestrictedAccess
dc.sourceCivil-Comp Proceedings
dc.subjectArtificial neural networken
dc.subjectDamen
dc.subjectDeformationen
dc.subjectMultiple linear regressionen
dc.subjectPredictionen
dc.subjectTemperatureen
dc.subjectWater levelen
dc.titlePrediction of concrete dam deformation using artificial neural networksen
dc.typeconferenceObject
dc.rights.licenseARR
dc.citation.other109: -
dc.citation.volume109
dc.identifier.rcubconv_2158
dc.identifier.scopus2-s2.0-84966293700
dc.type.versionpublishedVersion


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