The use of neural networks for the prediction of wear loss and surface roughness of AA 6351 aluminium alloy
| dc.contributor.author | Durmus, HK | |
| dc.contributor.author | Özkaya, E | |
| dc.contributor.author | Meriç, C | |
| dc.date.accessioned | 2024-07-18T11:47:10Z | |
| dc.date.available | 2024-07-18T11:47:10Z | |
| dc.description.abstract | Artificial 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. (c) 2004 Elsevier Ltd. All rights reserved. | |
| dc.identifier.issn | 0264-1275 | |
| dc.identifier.other | 1873-4197 | |
| dc.identifier.uri | http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/3323 | |
| dc.language.iso | English | |
| dc.publisher | ELSEVIER SCI LTD | |
| dc.subject | LITHIUM ADDITIONS | |
| dc.subject | PRECIPITATION | |
| dc.subject | CAST | |
| dc.title | The use of neural networks for the prediction of wear loss and surface roughness of AA 6351 aluminium alloy | |
| dc.type | Article |