This repository provides code for the experiments in: "Towards Sustainable Power Systems: Exploring the Opportunities of Multi-task Learning for Battery Degradation Forecasting": https://link.springer.com/chapter/10.1007/978-3-031-61069-1_9
Before running experiments, make sure the required dependencies are installed:
pip install -r requirements.txt
To run the experiments on your own device, make sure to unpack all files (folders as well).
The results of the experiments will be automatically logged to Weights and Biases https://wandb.ai/site. Make sure to create an account before starting the experiments.
To run benchmark experiments with different dynamic weighting algorithms on the "Battery Aachen dataset", run the run_experiments.py file.
Before running the code, specify the configuration in the dictionary provided in the run_experiments.py file. The meaning of each parameter is discussed below.