Determination of preconsolidation pressure with artificial neural network

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dc.contributor.authorCelik, S
dc.contributor.authorTan, O
dc.date.accessioned2020-03-26T16:56:50Z
dc.date.available2020-03-26T16:56:50Z
dc.date.issued2005
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThe correct determination of preconsolidation pressure is significantly important for settlement analysis in clay deposits. Many graphical methods have been developed by researchers for determining of preconsolidation pressure up to date. Some of these methods are Casagrande, Tavenas, Butterfield, Schmertmann and Janbu. Over the last few years, the use of artificial neural network (ANN) has increased in many areas of engineering. In particular, ANNs have been applied to many geotechnical engineering problems and have demonstrated some degree of success. In this study, using professional software called Statistica, an ANN model was developed to determine preconsolidation pressures in clay soils. Results from the model and graphical methods (Casagrande, Tavernas, and Butterfield) were compared with actual (experimental) preconsolidation pressures and each other. In comparison with the statistical results of the graphical methods, the ANN model yielded larger determination coefficient (R-2 = 0.961), lower standard deviation ratio (0.198), lower mean absolute error (36.933) and lower root mean square error (48.169).en_US
dc.identifier.doi10.1080/10286600500383923en_US
dc.identifier.endpage231en_US
dc.identifier.issn1028-6608en_US
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage217en_US
dc.identifier.urihttps://dx.doi.org/10.1080/10286600500383923
dc.identifier.urihttps://hdl.handle.net/20.500.12395/19660
dc.identifier.volume22en_US
dc.identifier.wosWOS:000233870400003en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherTAYLOR & FRANCIS LTDen_US
dc.relation.ispartofCIVIL ENGINEERING AND ENVIRONMENTAL SYSTEMSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectartificial neural networken_US
dc.subjectpreconsolidationen_US
dc.subjectoverconsolidateden_US
dc.subjectclayen_US
dc.titleDetermination of preconsolidation pressure with artificial neural networken_US
dc.typeArticleen_US

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