Support vector machines framework for predicting the PVT properties of crude-oil systems

Engineering

• Crude Oil System 100%
• Support Vector Machine 100%
• Correlation 83%
• Petroleum Industry 50%
• Performance 50%
• Prediction 33%
• Porosity 16%
• Flow Regime 16%
• Reservoir Fluid 16%
• Comparative Study 16%
• Minimization 16%
• Nonlinear Problem 16%
• Nonlinear Regression 16%
• Geographical Area 16%
• Data-Mining Technique 16%
• Liquid Holdup 16%
• Models 16%
• Engineering 16%
• Petroleum Engineering 16%
• Demonstrates 16%
• Fields 16%
• Characteristics 16%
• Fluid 16%
• Limitations 16%
• Empirical Correlation 16%
• Research 16%
• Algorithm 16%
• Accuracy 16%
• Hyperplanes 16%

Chemical Engineering

• Support Vector Machine 100%
• Neural Network 66%
• Learning System 16%