PREDICTION AND ANALYSIS OF KARST COLLAPSE WITH ENTROPY-NORMAL CLOUD MODEL

This paper studies the karst collapse prediction method in the karst area. It bases on a large number of karst collapse examples. It identifies six typical influencing factors in the karst area. They are lithology coefficient(RQC), rock mass structure coefficient(RMSC), groundwater coefficient(GWC), overlap factor(SSC), topographic coefficient(LPC) and environmental condition factor(ECC). It combines the cloud theory to establish an entropy weight normal cloud model. The model can predict the possibility of collapse in the karst area by calculating the weight of each impact factor in the subsidence area. The model is used to predict the data before the collapse of the karst collapse in the west of Guilin. The prediction result is close to the actual collapse. This proves that the model has good applicability and reliability for karst collapse prediction analysis. It provides new method for predicting and judging the nonlinearity and complexity of karst collapse in karst development areas.