The use of neural networks for the prediction of wear loss and surface roughness of AA 6351 aluminium alloy

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dc.contributor.authorDurmuş H.K.
dc.contributor.authorÖzkaya E.
dc.contributor.authorMeriç C.
dc.date.accessioned2024-07-22T08:23:37Z
dc.date.available2024-07-22T08:23:37Z
dc.date.issued2006
dc.description.abstractArtificial neural networks (ANNs) are a new type of information processing system based on modeling the neural system of human brain. Effects of ageing conditions at various temperatures, load, sliding speed, abrasive grit diameter in 6351 aluminum alloy have been investigated by using artificial neural networks. The experimental results were trained in an ANNs program and the results were compared with experimental values. It is observed that the experimental results coincided with ANNs results. © 2004 Elsevier Ltd. All rights reserved.
dc.identifier.DOI-ID10.1016/j.matdes.2004.09.011
dc.identifier.issn02613069
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/19620
dc.language.isoEnglish
dc.publisherElsevier Ltd
dc.subjectaluminum alloy
dc.subjectneural network
dc.subjectSurface roughness
dc.subjectAge hardening
dc.subjectMathematical models
dc.subjectMechanical testing
dc.subjectNeural networks
dc.subjectSurface roughness
dc.subjectWear of materials
dc.subjectWear loss
dc.subjectWear testing
dc.subjectAluminum alloys
dc.titleThe use of neural networks for the prediction of wear loss and surface roughness of AA 6351 aluminium alloy
dc.typeArticle

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