Abstract The coal mine flood is one of five nature disasters in the mine construction and production process. During the past 20 years, more than 250 mines were flooded, and the direct economic losses reached as high as more than 350 hundred million Yuan. In this article, the regional arrangement of sensors in the face of the program, considering the water level roadway, aquifer water levels, the top and bottom side pressure and the amount of water before driving and other factors, in combination with hydro-geological information and monitoring data, based on BP neural network and DS theory of levels of evidence coal face integration evaluation model of water bursting. It has been carried on the example analysis in the ore 3# coal bed in Shanxi, the results of prediction in line with the actual results, and different conditions for many parameters of the mine statistics, storage and evaluation.
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