Trains an initial LSTM autoencoder (Model A) on the full preprocessed dataset. Optionally trains a second LSTM autoencoder (Model B) on a "cleaned" dataset, from which anomalies identified by Model A ...

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Methods: This study integrates rainfall, surface displacement, and vertical displacement monitoring data, and proposes an automatic failure mode identification method based on deep convolutional ...