PM2.5-GNN

PM2.5-GNN: A Domain Knowledge Enhanced Graph Neural Network For PM2.5 Forecasting

Dataset

• Download dataset KnowAir from Google Drive or Baiduyun with code 2mr6.

Requirements

pip install -r requirements.txt

Experiment Setup

open config.yaml, do the following setups.

• set data path after your server name. Like,

filepath:
  GPU-Server:
    knowair_fp: /data/wangshuo/haze/pm25gnn/KnowAir.npy
    results_dir: /data/wangshuo/haze/pm25gnn/results

• Uncomment the model you want to run.

#  model: MLP
#  model: LSTM
#  model: GRU
#  model: GC_LSTM
#  model: nodesFC_GRU
   model: PM25_GNN
#  model: PM25_GNN_nosub

• Choose the sub-datast number in [1,2,3].

 dataset_num: 3

• Set weather variables you wish to use. Following is the default setting in the paper. You can uncomment specific variables. Variables in dataset KnowAir is defined in metero_var.

  metero_use: ['2m_temperature',
               'boundary_layer_height',
               'k_index',
               'relative_humidity+950',
               'surface_pressure',
               'total_precipitation',
               'u_component_of_wind+950',
               'v_component_of_wind+950',]

Run

python train.py