The use of neural networks for the prediction of swell pressure

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dc.contributor.authorErzin, Y
dc.date.accessioned2024-07-18T11:39:22Z
dc.date.available2024-07-18T11:39:22Z
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, 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.issn2005-307X
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/1572
dc.language.isoEnglish
dc.publisherTECHNO-PRESS
dc.subjectFUZZY MODEL
dc.subjectCAPACITY
dc.subjectBEHAVIOR
dc.titleThe use of neural networks for the prediction of swell pressure
dc.typeArticle

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