Multiple-factor based sparse urban travel time prediction

Keyphrases

• Link Travel Time 100%
• Travel Time Prediction 100%
• Urban Travel Time 100%
• Travel Time 75%
• Number of Neurons 50%
• Probe Vehicle 50%
• Artificial Neural Network Model 50%
• Real-time Traffic Information 25%
• Neural Network Model 25%
• Output Layer 25%
• Historical Data 25%
• Traffic Flow 25%
• Extracting Features 25%
• Traffic Pattern 25%
• Urban Road Network 25%
• Probe Vehicle Data 25%
• Neural Network Training 25%
• Result Prediction 25%
• Aggregate Data 25%
• Input Layer 25%
• Wuhan China 25%
• Weekly Cycle 25%
• Feature Relationship 25%
• Three-layer Neural Network 25%
• Working Day 25%
• Adjacent Link 25%

Computer Science

• Neural Network Model 100%
• Prediction Time 100%
• Artificial Neural Network 66%
• Historical Data 33%
• Traffic Pattern 33%
• Layer Neural Network 33%
• Time Traffic Data 33%
• Trained Neural Network 33%