Prediction of density, porosity and hardness in aluminum–copper-based composite materials using artificial neural network
- 19 January 2009
- journal article
- Published by Elsevier BV in Journal of the American Academy of Dermatology
- Vol. 209 (2), 894-899
- https://doi.org/10.1016/j.jmatprotec.2008.02.066
Abstract
No abstract availableThis publication has 17 references indexed in Scilit:
- Artificial neural networks in spectrum fatigue life prediction of composite materialsInternational Journal of Fatigue, 2007
- Effect of Graphite and/or Silicon Carbide Particles Addition on the Hardness and Surface Roughness of Al-4 wt% Mg AlloyJournal of Composite Materials, 2006
- A neural predictor to analyse the effects of metal matrix composite structure (6063 Al/SiCp MMC) on journal bearingIndustrial Lubrication and Tribology, 2006
- Corrosion behavior of Al–60 vol.% SiCp composites in NaCl solutionMaterials Letters, 2004
- Aging response of aluminium alloy 2024/silicon carbide particles (SiCp) compositesMaterials Science and Engineering: A, 2004
- Artificial neural network predictions on erosive wear of polymersWear, 2003
- Prediction on tribological properties of short fibre composites using artificial neural networksWear, 2002
- The use of neural networks for the prediction of fatigue lives of composite materialsComposites Part A: Applied Science and Manufacturing, 1999
- The influence of the hot deformation and heat treatment on the properties of P/M Al-Cu compositesJournal of the American Academy of Dermatology, 1996
- Artificial neural networks for the prediction of mechanical behavior of metal matrix compositesActa Metallurgica et Materialia, 1995