Jun 29, 2022 · This study proposes a new algorithm that combines Principal Component Analysis, Ensemble Empirical Mode Decomposition, Long Short-Term Memory Network

The results show that the short-term prediction effect of the PCA-EEMD-LSTM model is better than other models. Compared with the conventional landslide ...

A novel hybrid model based on PCA-EEMD-LSTM neural network for short-term landslide prediction · No full-text available · Citations (1) · References (17).

This study proposes a new algorithm that combines Principal Component Analysis, Ensemble Empirical Mode Decomposition, Long Short-Term Memory Network which ...

Aug 5, 2024 · Luo YH, Ran PY (2022) A novel hybrid model based on PCA-EEMD-LSTM neural network for short-term landslide prediction. In Proceedings of the ...

The proposed decomposition-ensemble learning model can be efficiently used to enhance the prediction accuracy of landslide displacement prediction and can also ...

Apr 5, 2024 · Compared with LSTM, the BPNN plays the performance of EEMD better, reduces the error to a certain extent, and improves the prediction accuracy.

Missing: PCA- | Show results with:PCA-

A Novel Decomposition-Ensemble Learning Model Based on Ensemble Empirical Mode Decomposition and Recurrent Neural Network for Landslide Displacement Prediction.

Missing: PCA- landslide