A novel surface deformation prediction method based on AWC-LSTM model
Severe surface deformation can damage the ecological environment, trigger geological disasters, and threaten human life and property. Reliable surface deformation prediction is conducive to reducing potential risks and mitigating disaster losses. Currently, machine learning-based surface deformation...
Saved in:
| Main Authors: | Yu Chen, Xinlong Chen, Shanchuan Guo, Huaizhan Li, Peijun Du |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843224006484 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sea Surface Temperature Prediction Using ConvLSTM-Based Model with Deformable Attention
by: Benyun Shi, et al.
Published: (2024-11-01) -
Research on prediction of surrounding rock deformation and optimization of construction parameters of high ground stress tunnel based on WOA-LSTM
by: Jianquan Yao, et al.
Published: (2024-11-01) -
A Multi-Point Correlation Model to Predict and Impute Earth-Rock Dam Displacement Data for Deformation Monitoring
by: Lilang Pi, et al.
Published: (2024-11-01) -
Breast cancer classification based on hybrid CNN with LSTM model
by: Mourad Kaddes, et al.
Published: (2025-02-01) -
A novel ensemble ARIMA‐LSTM approach for evaluating COVID‐19 cases and future outbreak preparedness
by: Somit Jain, et al.
Published: (2024-12-01)