Machine Learning Methods for Predicting Mechanical Behavior of Aluminum Alloys

Keyphrases

• AA6061-T6 40%
• Aluminum Alloy 100%
• Error Percentage 20%
• Gaussian Process Regression 20%
• Gradient Boosting Decision Tree 20%
• Machine Learning Techniques 100%
• Material Behavior 20%
• Mean Absolute Error 20%
• Mechanical Behavior 100%
• Metallic Materials 20%
• Neural Network Model 20%
• Plastic Behavior 20%
• Prediction Accuracy 20%
• Regression Neural Network 20%
• Statistical Scores 20%
• Stress Measurement 40%
• Stress-strain 40%
• Stress-strain Curve 40%
• Stress-strain Response 20%
• Temperature Level 20%
• Three-machine 20%
• Uniaxial Tensile Test 20%

Material Science

• Aluminum Alloys 100%
• Mechanical Property 100%
• Metal 50%
• Plasticity 50%
• Stress-Strain Measurement 100%
• Stress-Strain Relations 50%
• Tensile Testing 50%

Engineering

• Gaussians 20%
• Machine Learning Method 100%
• Mean Absolute Error 20%
• Network Model 20%
• Strain 40%
• Stress-Strain Curve 40%
• Stress-Strain Relations 20%
• Tensile Testing 20%