Travel Time Prediction Using Hybridized Deep Feature Space and Machine Learning Based Heterogeneous Ensemble

Computer Science

• Feature Space 100%
• Deep Feature 100%
• Prediction Time 100%
• Machine Learning 100%
• Learning System 100%
• Support Vector 20%
• Long Short-Term Memory Network 10%
• Data Source 10%
• Convolutional Neural Network 10%
• Deep Learning Model 10%
• Mean Absolute Error 10%
• Feature Reduction 10%
• Gated Recurrent Unit 10%
• Principal Components 10%
• Component Analysis 10%
• Multilayer Perceptron 10%
• Architectural Design 10%

Mathematics

• Feature Space 100%
• Absolute Error 20%
• Regressors 20%
• Support Vector Machine 20%
• Mean Square Error 10%
• Determination Coefficient 10%
• Ensemble Model 10%
• Data Source 10%
• Multilayer Perceptron 10%
• Test Data 10%
• Nonlinearity 10%
• Principal Component Analysis 10%
• Deep Learning Method 10%
• Convolutional Neural Network 10%