竖井揭煤瓦斯突出预测指标的优选

Vertical Shaft Coal Uncovering Gas Outburst Prediction Index Optimization

为了提高对竖井揭煤煤与瓦斯突出危险进行预测的准确性,选定煤层厚度、实测瓦斯压力、煤层埋深、打钻动力现象、钻孔瓦斯流量5个指标作为预测煤与瓦斯突出的变量,依据模糊神经网络理论,对变量进行模糊化处理,建立煤与瓦斯突出预测的模糊神经网络,并对样本进行训练和检验,所建立的模糊神经网络预测系统具有很高的预测精度,所预测结果满足工程实践要求。

In order to improve the coal and gas outburst along the shaft uncovering, coal seam thick, gas pressure prediction aecurang, coal seam bury depth, drilling power phenomenon, drilling gas flow, 5 indexes were taken as variables to predict coal and gas outburst, based on the obscure neural network theory, the variable was dealt obscurely, obscure neural network prediction of coal and gas outburst was constructed, the sample was trained and tested, the constructed obscure neural network prediction was accurate, the predicting outcomes met the needs of engineering practice requirements.