FCDNet: Frequency-Guided Complementary Dependency Modeling for Multivariate Time-Series Forecasting

Requirements

Python 3.8.3
see requirements.txt

Data Preparation

TXT File

Download Solar-Energy datasets from https://github.com/laiguokun/multivariate-time-series-data. Put into the data/{solar_AL} folder.

NPZ File

Download PEMS03, PEMS04, PEMS07, PEMS08 datasets from [https://github.com/Davidham3/ASTGCN/tree/master/data). Put into the data/{PEMS03,PEMS04,PEMS07,PEMS08} folder.

Split dataset

Run the following commands to generate train/validation/test dataset at data/{solar_AL,PEMS03,PEMS04,PEMS07,PEMS08}/{train,val,test}.npz.

python generate_data.py --dataset PEMS03 --train_rate 0.6 --val_rate 0.2

python generate_data.py --dataset PEMS04 --train_rate 0.6 --val_rate 0.2

python generate_data.py --dataset PEMS07 --train_rate 0.6 --val_rate 0.2

python generate_data.py --dataset PEMS08 --train_rate 0.6 --val_rate 0.2

python generate_data.py --dataset Solar_AL

Train Commands

Solar-Energy

# Use Solar-Energy dataset
python train.py --dataset_dir=data/solar_AL

PEMS03

# Use PEMS03 dataset
python train.py --dataset_dir=data/PEMS03

PEMS04

# Use PEMS04 dataset
python train.py --dataset_dir=data/PEMS04

PEMS07

# Use PEMS07 dataset
python train.py --dataset_dir=data/PEMS07

PEMS08

# Use PEMS08 dataset
python train.py --dataset_dir=data/PEMS08

Citation Format

If you find this codebase helpful for your research, please consider citing the following paper:

@article{chen2023fcdnet,
  title={FCDNet: Frequency-Guided Complementary Dependency Modeling for Multivariate Time-Series Forecasting},
  author={Chen, Weijun and Wang, Heyuan and Tian, Ye and Guan, Shijie and Liu, Ning},
  journal={arXiv preprint arXiv:2312.16450},
  year={2023}
}

Note: The reason for the voluntary withdrawal of our paper from Neural Networks, after it was accepted, was due to a dispute over the order of authors. This withdrawal is unrelated to the content of the paper itself.

onceCWJ/FCDNet