Modeling Dynamic Spatio-Temporal Correlations for Urban Traffic Flows Prediction

Keyphrases

• Application Domain 50%
• Bike 50%
• City Scale 100%
• Competitive Performance 50%
• Crowd Flow 50%
• Crowd Flow Prediction 50%
• Crowd Movement 50%
• Deep Hybrid Neural Networks 50%
• Dynamic Spatio-temporal Correlations 100%
• Existing State 50%
• External Branches 50%
• Large-scale Dataset 50%
• Model Dynamics 100%
• Network Unit 50%
• New York 50%
• Residual Neural Network 50%
• Spatial Dependence 50%
• Spatio-temporal Features 50%
• Spatiotemporal 50%
• Temporal Correlation 50%
• Temporal Dependence 50%
• Traffic Flow 100%
• Traffic Flow Prediction 100%
• Transportation Scheduling 50%
• Urban Management 50%
• Urban Traffic Flow 100%

Computer Science

• Application Domain 50%
• Neural Network 50%
• Residual Neural Network 50%
• Temporal Correlation 100%
• Temporal Feature 50%
• Traffic Flow Prediction 100%