HduDBSI / DSTGCN

Dynamic Attention And Trajectory Cognition Based Graph Convolution Network For Traffic Flow Forecasting

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DSTGCN

This is the repository of our paper "Dynamic Attention And Trajectory Cognition Based Graph Convolution Network For Traffic Flow Forecasting" and it is implemented in Pytorch. Some baselines are also implemented in this repository.

Requirements

  • matplotlib 3.3.3
  • numpy 1.18.5
  • pandas 1.2.2
  • scikit-learn 1.0.1
  • scipy 1.6.0
  • statsmodels 0.13.0
  • torch 1.2.0
  • tqdm 4.62.3

Baselines & How to run

baseline
HA python ARIMA/Arima_Main.py
ARIMA python HA/HA_main.py
SVR python SVR/SVR_main.py
LightGBM python Lightgbm/Lightgbm_main.py
STGCN python train_zhengzhou.py
ASTGCN python train_zhengzhou.py

all results will be printed to console

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Dynamic Attention And Trajectory Cognition Based Graph Convolution Network For Traffic Flow Forecasting


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