humcasma / kdd2019deeptcn

Probabilistic Forecasting with Temporal Convolutional Neural Network

Source codes for the paper "probabilistic forecasting with temporal convolutional neural network"

Electricity

Data preprocessing

• Download the dataset from UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/ElectricityLoadDiagrams20112014
• Run "R CMD BATCH electricity/basicPreprocess.R" to generate "modelData.csv" for model training.

Point forecasting

• python3 electricity/ecPointModel/ec_feature_preprocess.py
• python3 electricity/ecPointModel/ECPointHuber.py

Probabilistic forecasting

• python3 electricity/NewTCNQuantile/ec_feature_preprocess.py
• python3 electricity/NewTCNQuantile/ec_probabilistic_forecasting.py

Traffic

Data preprocessing

• Download the dataset from UCI Machine Learning Repository: https://archive.ics.uci.edu/ml/datasets/PEMS-SF
• Run "R CMD BATCH traffic/basicPreprocess.R" to generate "traffic.csv".
• python3 traffic/traffic_feature_preprocess.py to generate the "tensor_prepare.pkl" for the model training

Point forecasting

• python3 traffic/point/traffic_point_forecasting.py

Quantile regression

• python3 traffic/quantile/traffic_quantile_forecasting.py

Probabilistic forecasting

Parts

Data preprocessing

Probabilistic forecasting

Reference Paper

Probabilistic forecasting with temporal convolutional neural network

KDD 2019 ,Workshop on Mining and Learning from Time Series, 2019

Kind remind

The total project will be refined in the next months. Also, you can achieve better results if you do better data preprocessing like scaling.