Fig. 2: Numerical simulation and experimental data used in the transfer learning analysis. | Nature Communications

Fig. 2: Numerical simulation and experimental data used in the transfer learning analysis.

From: Predicting fault slip via transfer learning

Fig. 2

The top row shows the deep learning model input signal as the kinetic energy and acoustic emissions, respectively, and the bottom row shows the target friction coefficient. a Finite-discrete element method (FDEM) time series are split into training/validation/testing segments (60/20/20%) shown in green, blue, and pink shades, respectively. The convolutional encoder-decoder is fully trained and tested using these data. b The experimental data (p4677) are split into training/validation/testing segments (20/20/60%) to include six cycles of stick-slip events for training the model latent space.

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