Open access
Jul 2026
A Comprehensive Database and Smart-Learning Framework for Monitoring Failure Risk Factors, Maintenance, and Protection in Electrical Networks
A software-based database-generation and smart-learning framework that converts 22 candidate risk factors into six normalized severity levels and then maps the simultaneous system state to low-, medium-, and high-level protection decisions, supporting early fault detection, maintenance planning, and resilience improvement in renewable-integrated electrical networks is introduced.
A. Elasyri, Nazım İmal, M. Fidan
· Energies · 0 citations