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This research aims to enhance the reconstruction of mining-induced subsidence basins by integrating advanced inversion techniques and radar data fusion.

August 7, 2026Applied SciencesOpen Access

Complete Mining-Induced Subsidence Basin Reconstruction via Improved RIME-Based Probability Integral Parameter Inversion and SBAS-InSAR Residual Fusion

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QGQi GuoXi'an University of Science and Technology CQChunxia QiuXi'an University of Science and Technology

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Implication

Randomized trial demonstrates improved subsidence reconstruction in coal mines, suggesting enhanced accuracy in geophysical measurements.

Key Points

This research aims to enhance the reconstruction of mining-induced subsidence basins by integrating advanced inversion techniques and radar data fusion.
Developed a basin-reconstruction framework combining probability integral method (PIM) and improved RIME algorithm with SBAS-InSAR.
Utilized Sobol initialization and nonlinear adaptive search for improved convergence in parameter inversion.
Applied residual fusion to integrate subsidence intensity from both PIM and SBAS-InSAR for precise local corrections.
Achieved an RMSE of 66.7 ± 1.3 mm with RIME, representing 1.9% of maximum measured subsidence.
Fused model yielded an RMSE of 43 mm, reducing PIM-only errors by 33.85% and MAE by 51.92%.
Provided a coefficient of determination (R2) of 0.990 ± 0.001, highlighting high predictive accuracy.

Cite This Study

Guo et al. (2026) studied this question.

synapsesocial.com/papers/6a758c0f847ab6d26c01fdbf https://doi.org/10.3390/app16157782

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Complete Mining-Induced Subsidence Basin Reconstruction via Improved RIME-Based Probability Integral Parameter Inversion and SBAS-InSAR Residual Fusion

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Cite This Study

Complete Mining-Induced Subsidence Basin Reconstruction via Improved RIME-Based Probability Integral Parameter Inversion and SBAS-InSAR Residual Fusion

Discussion

Member takes

Implication

Key Points

Cite This Study

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