Communication-Efficient Design of Learning System for Energy Demand Forecasting of Electrical Vehicles

no code implementations • 4 Sep 2023 • Jiacong Xu, Riley Kilfoyle, Zixiang Xiong, Ligang Lu

In this paper, we propose a communication-efficient time series forecasting model combining the most recent advancements in transformer architectures implemented across a geographically dispersed series of EV charging stations and an efficient variant of federated learning (FL) to enable distributed training.

Federated Learning Time Series +2