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Application of artificial neural networks for slope stability analysis in geotechnical practice
dc.creator | Kostić, Srđan | |
dc.creator | Vasović, Nebojša | |
dc.creator | Todorović, Kristina | |
dc.creator | Samčović, Andreja | |
dc.date.accessioned | 2019-09-02T11:54:07Z | |
dc.date.available | 2019-09-02T11:54:07Z | |
dc.date.issued | 2016 | |
dc.identifier.uri | https://farfar.pharmacy.bg.ac.rs/handle/123456789/2672 | |
dc.description.abstract | In 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.publisher | IEEE, New York | |
dc.relation | info:eu-repo/grantAgreement/MESTD/Basic Research (BR or ON)/176016/RS// | |
dc.rights | restrictedAccess | |
dc.source | 2016 13th Symposium on Neural Networks and Applications, NEUREL 2016 | |
dc.subject | artificial neural network | en |
dc.subject | safety factor | en |
dc.subject | slope stability | en |
dc.subject | verification | en |
dc.title | Application of artificial neural networks for slope stability analysis in geotechnical practice | en |
dc.type | conferenceObject | |
dc.rights.license | ARR | |
dcterms.abstract | Васовић, Небојша; Тодоровић, Кристина; Самцовић, Aндреја; Костић, Срдан; | |
dc.citation.spage | 89 | |
dc.citation.epage | 94 | |
dc.citation.other | : 89-94 | |
dc.identifier.wos | 000391930100020 | |
dc.identifier.doi | 10.1109/NEUREL.2016.7800125 | |
dc.identifier.scopus | 2-s2.0-85010876754 | |
dc.type.version | publishedVersion |
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