Prediction of remained pillar against water-inrush from fault by using BP and RBF neural networks

On the basis of summing up the relevant information of the safety pillar against water-inrush from fault in typical coal mines throughout the country, taking head pressure, coal seam thickness, safe coefficient, coal tensile strength as the main influence factors, choosing the representative sample data, we built the BP and RBF neural network model through the Matlab software, with the model we forecasted the designed width of the water-proof coal pillar in each coal mine. Compared with the calculated results of procedure empirical formula, on the research of the design about water-proof pillar from coalfield, we found that it was faster for RBF neural networks in training speed than the BP neural networks, furthermore, RBF is much more efficient than BP and can get broader application prospects.