Feasibility analysis of the application of the Hossfeld model for the prediction of dynamic subsidence in mining areas

The use of time models for subsidence prediction is one of the most commonly methods for predicting dynamic deformation in coal mining areas. Based on analyzing the existence of time-zero problems in typical time function models, this paper introduces a Forest Growth Model （i.e., the Hossfeld model）, and analyzes the prediction accuracy of the Hossfeld model for the subsidence prediction at a single point and an arbitrary points in the coal mining subsidence basin by using the leveling data and the D-InSAR results, and evaluates the correlation of the model parameters. The results show that in the prediction results of single-point subsidence from leveling data, the accuracy of Knothe and Usher models with corrected time-zero is higher than that of Knothe and Usher models with uncorrected time-zero; the proportion of the subsidence prediction results with the RMSE<100 mm from the Hossfeld model is slightly lower than that of the Usher model with corrected time-zero, higher than that of the Usher model with uncorrected time-zero, and much higher than that of the Knothe time function model with corrected and uncorrected time-zero; the Hossfeld model has the highest accuracy in the MAE <100 mm; in the prediction results of arbitrary points subsidence from D-InSAR technology observation, the statistical correlations of the parameters used to construct the dynamic prediction model show that the Hossfeldmodel is the most coherent; further, the calculation of the Bland-Altman shows that the difference between the results of the Hossfeld model and the D-InSAR results is relatively small and has the highest accuracy at RMSE and MAE <20 mm. Compared with Knothe model and Usher model, the Hossfeld model has obvious advantages in accuracy for dynamic subsidence prediction because it does not require time-zero correction.