The D-CNN-LSTM Autoencoder method optimizes the anomaly detection rate for all of the anomalies, specifically in the case of low magnitude anomalies, enhancing F1-score up to 18.12% in single types of ...

The proposed lightweight LSTM- and GRU-based neural networks are extensively validated using a 2.2-kW interior permanent-magnet synchronous motors through simulations and experiments for estimating ...