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dc.creatorRadovanović, Slobodan
dc.creatorRanković, Vesna
dc.creatorAnđelković, Vladimir
dc.creatorDivac, Dejan
dc.creatorMilivojević, Nikola
dc.date.accessioned2019-04-19T14:29:38Z
dc.date.available2019-04-19T14:29:38Z
dc.date.issued2018
dc.identifier.issn1435-9529
dc.identifier.urihttp://grafar.grf.bg.ac.rs/handle/123456789/942
dc.description.abstractKnowledge of the deformation properties of the rock mass is essential for the stress-strain analysis of structures such as dams, tunnels, slopes, and other underground structures and the most important parameter of the deformability of the rock mass is the deformation modulus. This paper describes statistical models based on multiple linear regression and artificial neural networks. The models are developed using the test results of the deformation modulus obtained during the construction of the Iron Gate 1 dam on the Danube River and correlate these with measurements of the velocities of longitudinal waves and pressures in the rock mass. The parameters used for defining the models were obtained by in situ testing during dam construction, meaning that scale effects were also taken into account. For the analysis, 47 experimental results from in situ testing of the rock mass were obtained; 38 of these were used for modelling and nine were used for testing of the models. The model based on the artificial neural networks showed better performance in comparison to the model based on multiple linear regression.en
dc.publisherSpringer Verlag
dc.relationinfo:eu-repo/grantAgreement/MESTD/Technological Development (TD or TR)/37013/RS//
dc.rightsrestrictedAccess
dc.sourceBulletin of Engineering Geology and the Environment
dc.subjectDeformation modulus of rock massesen
dc.subjectVelocities of longitudinal wavesen
dc.subjectRock mass pressuresen
dc.subjectIn situ testingen
dc.subjectMultiple linear regressionen
dc.subjectArtificial neural networksen
dc.titleDevelopment of new models for the estimation of deformation moduli in rock masses based on in situ measurementsen
dc.typearticle
dc.rights.licenseARR
dc.citation.epage1202
dc.citation.issue3
dc.citation.other77(3): 1191-1202
dc.citation.rankM22
dc.citation.spage1191
dc.citation.volume77
dc.identifier.doi10.1007/s10064-017-1027-2
dc.identifier.rcubconv_1991
dc.identifier.scopus2-s2.0-85014071698
dc.identifier.wos000441525900026
dc.type.versionpublishedVersion


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