Uncovering critical determinants of fault severity in smart power networks by integrating automatic algorithms
This study introduces a shift from traditional classification toward regression‑based prediction of fault severity through a novel integration of Support Vector Regression and Histogram‑Based Gradient Boosting, forming a scalable tool for continuous fault monitoring and strengthens grid resilience by enabling proactive maintenance strategies.