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dc.creatorKostić, Srđan
dc.creatorVasović, Nebojša
dc.creatorTodorović, Kristina
dc.creatorSamčović, Andreja
dc.date.accessioned2019-09-02T11:54:07Z
dc.date.available2019-09-02T11:54:07Z
dc.date.issued2016
dc.identifier.urihttps://farfar.pharmacy.bg.ac.rs/handle/123456789/2672
dc.description.abstractIn present paper, authors develop a model for estimation of earth slope stability based on the artificial neural networks. For this purpose, authors engage multi-layer feed-forward network with Levenberg-Marquardt learning algorithm and 14 hidden nodes, using existing experimental data, and the results of traditional limit equilibrium analyzes of 57 different cases according to the predefined experimental plan. The results obtained indicate high level of statistical reliability (R=0.95 and MSE=0.0035 for testing set of scaled values) and similar estimation accuracy as the existing mathematical expression for calculation of slope safety factor.en
dc.publisherIEEE, New York
dc.relationinfo:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/176016/RS//
dc.rightsrestrictedAccess
dc.source2016 13th Symposium on Neural Networks and Applications, NEUREL 2016
dc.subjectartificial neural networken
dc.subjectsafety factoren
dc.subjectslope stabilityen
dc.subjectverificationen
dc.titleApplication of artificial neural networks for slope stability analysis in geotechnical practiceen
dc.typeconferenceObject
dc.rights.licenseARR
dcterms.abstractВасовић, Небојша; Тодоровић, Кристина; Самцовић, Aндреја; Костић, Срдан;
dc.citation.spage89
dc.citation.epage94
dc.citation.other: 89-94
dc.identifier.wos000391930100020
dc.identifier.doi10.1109/NEUREL.2016.7800125
dc.identifier.scopus2-s2.0-85010876754
dc.type.versionpublishedVersion


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