Open access
Sep 2026
Residual-based ARIMA_CNN_LSTM modeling for borehole stress time-series forecasting
This research establishes are residual-based ARIMA–CNN–LSTM model for predicting borehole stress in non-stationary, nonlinear, and noise-affected monitoring situations. The ARIMA (2,1,5) initially models the foreseeable linear and autocorrelated part. Subsequently, a CNN–LSTM network captures short-term patterns and lo...
Jun Tang, Ting, Guo-Lin Guo et al.
· Acta geodynamica et geomater... · 0 citations