ABSTRACT
This study examines the detrimental effects of underground mining, particularly focusing on surface displacements and deformations. It highlights the consequences of these transformations in urban areas where buildings and critical infrastructure are at risk. The research investigates a stochastic model used for predicting land subsidence, specifically scrutinizing the accuracy related to the uncertainty of model parameters. The concept of the probability influence function is elucidated, describing its mathematical formulation and relevance to subsidence prediction. The parameters involved in the model are detailed, emphasizing their significance and dependency on geological and technical conditions. The statistical analysis assesses prediction accuracy concerning model parameters, discussing the Monte Carlo method and the law of error propagation to estimate the mean errors of deformation indicators due to inaccuracies in model parameters. Two practical examples are presented. The first involves determining the probability of exceeding harmful influence ranges in coal mining using calculated deformation indicators and statistical analyses. The second example examines coal exploitation in a residential area, assessing the resistance of buildings to deformation and the probability of exceeding strain limit values.
