Modeling the Relationship Between Maximum Subsidence Angle and Coal Seam Dip Angle for Predicting Ground Movement in Underground Mining

Khai Cong Pham

Abstract: This study develops regression-based models to predict the maximum subsidence angle as a function of coal seam dip angle for underground coal mining in the Quang Ninh coal basin, Vietnam. Data from representative mines were analyzed by separating seam dip conditions below and above 45 degrees. Five regression models were evaluated, including linear, logarithmic, polynomial, power, and exponential functions. Comparative accuracy assessment using Root Mean Squared Error showed that second-order polynomial regression provided the best predictive performance in both dip-angle groups, with RMSE values of approximately 0.72 degrees for dip angles below 45 degrees and 0.64 degrees for dip angles above 45 degrees. The developed models provide a practical tool for improving subsidence prediction, safety pillar design, and hazard zoning in underground mining operations.

Keywords: Underground mining, Ground subsidence, Subsidence prediction, Coal seam dip angle, Regression modeling, Rock mass deformation, Mining geomechanics