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

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

As vital comments on landslide early warning systems, accurate and reliable displacement prediction is essential and of significant importance for landslide mitigation. However, obtaining the desired prediction accuracy remains highly difficult and challenging due to the complex nonlinear characteri...

Full description

Bibliographic Details
Main Authors: Xiaoxu Niu, Junwei Ma, Yankun Wang, Junrong Zhang, Hongjie Chen, Huiming Tang
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Applied Sciences
Subjects:
landslide displacement prediction
decomposition-ensemble model
recurrent neural network (RNN)
ensemble empirical mode decomposition (EEMD)
maximal information coefficient (MIC)
Online Access:https://www.mdpi.com/2076-3417/11/10/4684

Internet

https://www.mdpi.com/2076-3417/11/10/4684

Similar Items