Unascertained measurement classifying model of goal collapse prediction

摘要

Based on optimized forecast method of unascertained classifying,a unascer- tained measurement classifying model (UMC) to predict mining induced goaf collapse was established,The discriminated factors of the model are influential factors including over- burden layer type,overburden layer thickness,the complex degree of geologic structure, the inclination angle of coal bed,volume rate of the cavity region,the vertical goaf depth from the surface and space superposition layer of the goaf region.Unascertained mea- surement (UM) function of each factor was calculated.The unascertained measurement to indicate the classification center and the grade of waiting forecast sample was determined by the UM distance between the synthesis index of waiting forecast samples and index of every classification.The training samples were tested by the established model,and the correct rate is 100%.Furthermore,the seven waiting forecast samples were predicted by the UMC model.The results show that the forecast results are fully consistent with the ac- tual situation.