SecFD-FL: Frequency-Decoupled Federated Learning with Secure Aggregation for Charging Load Forecasting in Internet of Electric Vehicles

arXiv:2610.12909 · eess.SY, cs.SY · Submitted 2026-10-09 · Read on arXiv

eess.SY, cs.SY

Submitted: 2026-10-09

Updated: 2026-10-09

Comments: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Aggregation — 1× in this paper · explained in 1 episode
• Federated Learning — 1× in this paper · explained in 16 episodes

Sources

• Federated Learning with Non-IID Data
• Adaptive Federated Optimization
• Federated Learning Based on Dynamic Regularization

Related papers

• One Request, Multiple Experts: LLM Orchestrates Domain Specific Models via Adaptive Task Routing
• A Geometric Decision Procedure for STL Feasibility and Repair
• From Asymptotic to Designer-Assigned-Time Control: A Review of Stability Notions, Design Mechanisms, and Controller Architectures
• Battery Second Life: A Review of Experimental Studies
• Submodular Multi-Agent Policy Learning for Online Distributed Task Allocation in Open Multi-Agent Systems
• Policy-Level Recursive Self-Improvement for Embodied AI with a Criticality World Model