The aim of this project is to develop A Federated learning-based method to predict building energy consumption without data privacy leakage.
The operational data from 13 similar office buildings can be downloaded from the repository.
These codes should be processed on Google Colaboratory or Jupyter.
federated model optimization.ipynb is utilized to optimize the hyperparameters of the federated model.
fine-tune.py is utilized to fine-tune the federated model using local data.