Bridge data anomaly detection based on improved WGAN-GP and CBAM-Dense-DANN
Data anomaly detection based on machine learning models has been widely applied in bridge health monitoring systems to automatically identify anomalous monitoring data. However, its performance is often constrained by the randomness, scarcity, and limited distributional representativeness of known anomalous data. Thi...