Neural network based model for seismic assessment of existing RC buildings

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dc.authoridGarip, Zehra Sule/0000-0001-9268-3985
dc.authoridCaglar, Naci/0000-0003-4070-5534
dc.contributor.authorCaglar, Naci
dc.contributor.authorGarip, Zehra Sule
dc.date.accessioned2024-09-29T16:05:16Z
dc.date.available2024-09-29T16:05:16Z
dc.date.issued2013
dc.departmentKarabük Üniversitesien_US
dc.description.abstractThe objective of this study is to reveal the sufficiency of neural networks (NN) as a securer, quicker, more robust and reliable method to be used in seismic assessment of existing reinforced concrete buildings. The NN based approach is applied as an alternative method to determine the seismic performance of each existing RC buildings, in terms of damage level. In the application of the NN, a multilayer perceptron (MLP) with a back-propagation (BP) algorithm is employed using a scaled conjugate gradient. NN based model wasd eveloped, trained and tested through a based MATLAB program. The database of this model was developed by using a statistical procedure called P25 method. The NN based model was also proved by verification set constituting of real existing RC buildings exposed to 2003 Bingol earthquake. It is demonstrated that the NN based approach is highly successful and can be used as an alternative method to determine the seismic performance of each existing RC buildings.en_US
dc.identifier.doi10.12989/cac.2013.12.2.229
dc.identifier.endpage241en_US
dc.identifier.issn1598-8198
dc.identifier.issn1598-818X
dc.identifier.issue2en_US
dc.identifier.scopus2-s2.0-84883315879en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage229en_US
dc.identifier.urihttps://doi.org/10.12989/cac.2013.12.2.229
dc.identifier.urihttps://hdl.handle.net/20.500.14619/6613
dc.identifier.volume12en_US
dc.identifier.wosWOS:000324810800007en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTechno-Pressen_US
dc.relation.ispartofComputers and Concreteen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectneural networksen_US
dc.subjectscaled conjugate gradient algorithmen_US
dc.subjectrapid assessmenten_US
dc.subjectP25 methoden_US
dc.subjectexisting RC buildingsen_US
dc.titleNeural network based model for seismic assessment of existing RC buildingsen_US
dc.typeArticleen_US

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