Spatial Origin-Destination Flow Imputation Using Graph Convolutional Networks

Keyphrases

• Flow Data 100%
• Origin-destination Flows 100%
• Graph Convolutional Network 100%
• Prediction Accuracy 66%
• Spatial Flow 66%
• Negative Sampling 66%
• Geographic Unit 66%
• Data Collection Methods 33%
• Mapping Function 33%
• Sampling Methods 33%
• Network Model 33%
• Network Structure 33%
• Networked Learning 33%
• Spatial Networks 33%
• Connectivity Pattern 33%
• Negative Impact 33%
• Training Set 33%
• Sampling Rate 33%
• Privacy Concerns 33%
• Model Performance 33%
• Data Imputation 33%
• Spatial Interaction 33%
• Mobility Patterns 33%
• Training Samples 33%
• Low Performance 33%
• Graph Structure 33%
• Local Spatial 33%
• Misestimation 33%
• Flow Prediction 33%
• Interaction Graph 33%
• Taxi Trip Data 33%
• Graph Neural Network 33%

Computer Science

• Prediction Accuracy 100%
• Graph Convolutional Network 100%
• Learning Network 50%
• Performance Model 50%
• Lower Performance 50%
• Spatial Interaction 50%
• Sampling Rate 50%
• Data Collection Technique 50%
• Interaction Graph 50%
• Graph Neural Network 50%
• Training Sample 50%
• Structured Data 50%
• Mapping Function 50%
• Sampling Technique 50%
• Negative Impact 50%
• Graph Convolution 50%
• Network Structure 50%

Mathematics

• Graph Convolutional Network 100%