Genetic algorithm feature selection with Extra Trees reduces PMU features from 112 to an average of 27.4 while raising macro-F1 from 0.9118 to 0.9212 and ROC-AUC from 0.9791 to 0.9837 on the MSU/ORNL dataset.
S tudy of smart grid cyber-security, examining architectures, communication networks, cyber-attacks, coun- termeasure techniques, and challenges
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Cyber-Physical Anomaly Detection in IoT-Enabled Smart Grids Using Machine Learning and Metaheuristic Feature Optimization
Genetic algorithm feature selection with Extra Trees reduces PMU features from 112 to an average of 27.4 while raising macro-F1 from 0.9118 to 0.9212 and ROC-AUC from 0.9791 to 0.9837 on the MSU/ORNL dataset.