Integration of D-InSAR technology and PSO-SVR algorithm for time series monitoring and dynamic prediction of coal mining subsidence
Author:
Publisher
Informa UK Limited
Subject
Earth and Planetary Sciences (miscellaneous),Computers in Earth Sciences,Civil and Structural Engineering
Link
http://www.tandfonline.com/doi/pdf/10.1179/1752270614Y.0000000126
Reference27 articles.
1. Prediction of subsidence due to underground mining by artificial neural networks
2. Large-scale deformation monitoring in mining area by D-InSAR and 3D laser scanning technology integration
3. Practical selection of SVM parameters and noise estimation for SVM regression
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3. An Efficient and Fully Refined Deformation Extraction Method for Deriving Mining-Induced Subsidence by the Joint of Probability Integral Method and SBAS-InSAR;IEEE Transactions on Geoscience and Remote Sensing;2023
4. Time series monitoring and prediction of coal mining subsidence based on multitemporal InSAR technology and GSM-HW model;Journal of Applied Remote Sensing;2022-09-13
5. Integration of unmanned aerial vehicle (UAV)-based photogrammetry and InSAR for mining subsidence and parameters inversion: a case study of the Wangjiata Mine, China;Bulletin of Engineering Geology and the Environment;2022-08
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