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Deep spatio-temporal neural network based on interactive attention for traffic flow prediction

https://doi.org/10.1007/s10489-021-02879-1
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction
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Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting
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Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting
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Spatio-Temporal Recurrent Convolutional Networks for Citywide Short-term Crowd Flows Prediction
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AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction
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Intelligent Traffic Signal Control Based on Reinforcement Learning with State Reduction for Smart Cities
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Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
inferredcites →https://doi.org/10.1609/aaai.v32i1.11836openalex-snapshot
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
inferredcites →https://doi.org/10.1609/aaai.v33i01.33011020openalex-snapshot
DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis
inferredcites →https://doi.org/10.1609/aaai.v33i01.33015668openalex-snapshot
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Spatio-Temporal Factors Affecting Short-Term Public Transit Passenger Demand Prediction: A Review
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MSTMN: a novel meta-attention-based multi-task spatiotemporal network for traffic flow prediction
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A period-extracted multi-featured dynamic graph convolution network for traffic demand prediction
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FeSTGCN: A frequency-enhanced spatio-temporal graph convolutional network for traffic flow prediction under adaptive signal timing
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Causal graph convolution neural differential equation for spatio-temporal time series prediction
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Pedestrian flow prediction using a spatiotemporal multi-head attention graph convolutional network integrated with knowledge graph
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Multi-level spatial-temporal fusion neural network for traffic flow prediction
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Emerging Trends in Graph Neural Networks for Traffic Flow Prediction: A Survey
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Recent Advances in Multi-source Data Fusion for Traffic Flow Prediction: A Review
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Deep learning-based public transit passenger flow prediction model: integration of weather and temporal attributes
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