The use of artificial neural networks for the prediction of swell pressure

Simple item page
dc.contributor.authorErzin Y.
dc.date.accessioned2024-07-22T08:22:09Z
dc.date.available2024-07-22T08:22:09Z
dc.date.issued2008
dc.description.abstractArtificial neural networks (ANNs) are a new type of information processing system based on modeling the neural system of human brain. The prediction of swell pressures from easily determined soil properties, namely, initial dry density, initial water content, and plasticity index, have been investigated by using artificial neural networks. The results of the constant volume swell tests in oedometers (ASTM 1990), performed on statically compacted specimens of Bentonite-Kaolinite clay mixtures with varying soil properties, were trained in an ANNs program and the results were compared with the experimental values. It is observed that the experimental results coincided with ANNs results.
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/18955
dc.language.isoEnglish
dc.subjectBentonite
dc.subjectClay
dc.subjectData processing
dc.subjectGeomechanics
dc.subjectKaolinite
dc.subjectSoftware testing
dc.subjectSoil mechanics
dc.subjectClay mixtures
dc.subjectConstant volumes
dc.subjectDry density
dc.subjectExperimental values
dc.subjectHuman brain
dc.subjectInformation processing systems
dc.subjectNeural systems
dc.subjectOedometers
dc.subjectPlasticity indices
dc.subjectSoil property
dc.subjectSwell pressure
dc.subjectSwell test
dc.subjectNeural networks
dc.titleThe use of artificial neural networks for the prediction of swell pressure
dc.typeConference paper

Files

Collections

Scopus Koleksiyonu