Experimental Investigation and Artificial Neural Network Modeling of Warm Galvanization and Hardened Chromium Coatings Thickness Effects on Fatigue Life of AISI 1045 Carbon Steel

This publication has 30 references indexed in Scilit:

• Determination of the influence of processing parameters on the mechanical properties of the Ti–6Al–4V alloy using an artificial neural network
  Computational Materials Science, 2012
• Investigating Effect of Industrial Coatings on Fatigue Damage
  Applied Mechanics and Materials, 2011
• A neural network approach to fatigue life prediction
  International Journal of Fatigue, 2011
• Uncertainty analysis of a neural network used for fatigue lifetime prediction
  Mechanical Systems and Signal Processing, 2008
• Fatigue life prediction of composite materials using polynomial classifiers and recurrent neural networks
  Composite Structures, 2007
• Artificial neural networks in spectrum fatigue life prediction of composite materials
  International Journal of Fatigue, 2007
• Neural network application in fatigue damage analysis under multiaxial random loadings
  International Journal of Fatigue, 2006
• A neural network approach to describing the fretting fatigue in aluminium-steel couplings
  International Journal of Fatigue, 2003
• Artificial intelligence for the modeling and control of combustion processes: a review
  Progress in Energy and Combustion Science, 2003
• The use of neural networks for the prediction of fatigue lives of composite materials
  Composites Part A: Applied Science and Manufacturing, 1999