Open access
Apr 2026
Asynchronous federated learning with partial weights aggregation for energy consumption forecasting
An asynchronous federated learning framework for energy forecasting that enables continuous global model updating without waiting for all clients to complete local training is proposed and outperforms the classic FedAsync algorithm across all client groups.
Liana Toderean, Mara Mesesan, T. Cioara et al.
· Science in progress · 0 citations