Determining Predicting Parameters of Mining Subsidence Based on Fuzzy Optimization

摘要

The prediction precision of the ground movement and distortion in mines depends on the predicting parameters. According to the practical observational data from the ground movement monitoring stations of many mines in China, the fuzzy cluster analysis of the resembling phenomena clusters on mining subsidence is carried out by the similarity theory. The resembling phenomena on mining subsidence are approximately classified into three major sorts, and the second major sort is further classified into six subordinate sorts, and also, the parameters of the basic rock strata movement of mining subsidence are calculated out. Based on the classification of the mining subsidence resembling phenomena clusters and the strata movement parameters, the mining subsidence pattern of a new mine and its predicting parameters are determined by the fuzzy pattern recognition theory and the nearest principle. Considering the mining subsidence patterns B_1,B_2,…,B_n, if a new mining subsidence pattern C is the most closed to the mining subsidence pattern B_i (i=1,2,…,n), then the predicting parameters of the mining subsidence pattern B_i will be chosen as the ones of the new mining subsidence pattern C. The validity and reliability of the determining method of the mining subsidence predicting parameters are verified by the existing engineering instances.