The Feasibility of Mining Under a Water Body Based on a Fuzzy Neural Network

The burial depth and dip angle of a coal seam, the size of the working face, mining height, structure of the overlying strata, coal mining method, and the number of mining slices all significantly affect the amount of water flowing in a fractured zone. Combined with these seven factors, a predictive model for the height of water flowing in a fractured zone was established based on a fuzzy neural network, and 49 typical cases were chosen to train and test the network. The test error of the network was small and the match degree was high. Furthermore, the predicted height of water flowing in a fractured zone of working face 2309 in the Guozhuang coal mine, China was found to be within the range of the results calculated by more traditional (the empirical formula, the key stratum, and numerical simulation) predictive methods. After a safety coefficient of 1.2–1.5 was incorporated, a 183–211 m thick coal/rock safety pillar was required. In addition, a 98 m rock pillar with original permeability was left between the protective layer and the weathered zone. Therefore, under normal conditions, the mining of working face 2309 beneath Jianghe River was assessed to be safe and feasible.