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Found 4 papers, 0 papers with code
STDA-Meta: A Meta-Learning Framework for Few-Shot Traffic Prediction
As the development of cities, traffic congestion becomes an increasingly pressing issue, and traffic prediction is a classic method to relieve that issue.
Attention-based Dynamic Graph Convolutional Recurrent Neural Network for Traffic Flow Prediction in Highway Transportation
As one of the important tools for spatial feature extraction, graph convolution has been applied in a wide range of fields such as traffic flow prediction.
Phased Deep Spatio-temporal Learning for Highway Traffic Volume Prediction
Inter-city highway transportation is significant for citizens' modern urban life and generates heterogeneous sensory data with spatio-temporal characteristics.
Multi-graph Spatio-temporal Graph Convolutional Network for Traffic Flow Prediction
In our method, data normalization strategy is used to deal with data imbalance, due to long-tail distribution of traffic flow at network-wide toll stations.
