The usability of Cerchar abrasivity index for the prediction of UCS and E of Misis Fault Breccia: Regression and artificial neural networks analysis

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dc.authorid0000-0001-7903-143X
dc.authorid0000-0003-2488-7817
dc.contributor.authorKahraman, S.
dc.contributor.authorAlber, M.
dc.contributor.authorFener, M.
dc.contributor.authorGunaydin, O.
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2010
dc.departmentNiğde ÖHÜ
dc.description.abstractThe derivation of some predictive models for the geomechanical properties of fault breccias will be useful due to the fact that the preparation of smooth specimens from the fault breccias is usually difficult and expensive. To develop some predictive models for the uniaxial compressive strength (UCS) and elastic modulus (E) from the indirect methods including the Cerchar abrasivity index (CAI), regression and artificial neural networks (ANNs) analysis were applied on the data pertaining to Misis Fault Breccia. The CAI was included to the best regression model for the prediction of UCS. However, the CAI was not included to the best regression model for the prediction of E. The developed ANNs model was also compared with the regression model. It was concluded that the CAI is a useful property for the prediction of UCS of Misis Fault Breccia. Another conclusion is that ANNs model is more reliable than the regression models. (C) 2010 Elsevier Ltd. All rights reserved.
dc.description.sponsorshipAlexander von Humboldt Foundation
dc.description.sponsorshipThis study was supported by Alexander von Humboldt Foundation.
dc.identifier.doi10.1016/j.eswa.2010.06.039
dc.identifier.endpage8756
dc.identifier.issn0957-4174
dc.identifier.issue12
dc.identifier.scopus2-s2.0-77957849630
dc.identifier.scopusqualityQ1
dc.identifier.startpage8750
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2010.06.039
dc.identifier.urihttps://hdl.handle.net/11480/4822
dc.identifier.volume37
dc.identifier.wosWOS:000281339900156
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONS
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectFault breccia
dc.subjectUniaxial compressive strength
dc.subjectElastic modulus
dc.subjectPhysical and textural properties
dc.subjectCerchar abrasivity index
dc.subjectArtificial neural networks
dc.titleThe usability of Cerchar abrasivity index for the prediction of UCS and E of Misis Fault Breccia: Regression and artificial neural networks analysis
dc.typeArticle

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