A spatio-temporal predictive model for surface subsidence induced by mining in deep loose and thin bedrock strata

Aiming at the shortcomings and limitations of existing prediction methods and time function models in predicting the surface subsidence induced by coal mining in deep loose and thin bedrock strata, the deformation and mechanics characteristics of mining rock are analyzed comprehensively, and a near rectangular deflection function is established based on determining the spatial position of the primary key layer. Combining with the principle of probability integral method of discontinuous random medium, a spatio-temporal predictive model(SPM) is obtained to depict the development of surface subsidence throughout coal mining process, and its reliability is verified. The results demonstrate that the model can accurately invert the whole process of surface subsidence with coal mining, providing reliable outcomes. The model considers various factors relevant to coal mining, contributing to its theoretical significance. Additionally, the utilization of visual programming operations enhances the practicality and convenience of the model in engineering applications. The results are of great significance for the prevention and control of stratal subsidence disasters resulting from mining activities.