Using digital twin augmented data improved random forest and LSTM anomaly detection accuracy on a simulated power electronics dominated microgrid under a man-in-the-middle attack.
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Leveraging Digital Twin and Machine Learning Techniques for Anomaly Detection in Power Electronics Dominated Grid
Using digital twin augmented data improved random forest and LSTM anomaly detection accuracy on a simulated power electronics dominated microgrid under a man-in-the-middle attack.