【摘要】 利用煤巷掘进过程中所暴露出的大量的煤层信息,确定了与煤巷掘进前方小构造存在密切关系的影响因素,分析了煤层倾角、煤层厚度、涌水量、瓦斯等各个影响因子,选出主控因子,建立主控因子与煤巷掘进前方小构造预测危险性指数间的人工神经网络(ANN)分析模型,求取了各影响因素对前方小构造预测的权重系数,并建立了煤巷掘进前方小构造预测预报的ANN模型及其判据.对鹤壁十矿煤巷掘进前方小构造进行了预测,结果表明:ANN技术可用于煤矿巷道掘进前方小构造预测.更多还原

【Abstract】 Based on numerous extracted coal seam information,the influencing factors related to size-limited structures in the front of coal tunnelling were determined.On the basis of analysis of geological factors,the dominating factors on size-limited structures prediction were selected.The analysis model of the artificial neural network(ANN) between dominating factors and prediction index for size-limited structures was built.The value of the complication coefficients was obtained,and a predicted model of size-limited structures in the front of coal tunnelling was proposed.Finally,the model was applied to the prediction of size-limited structures in the front of coal tunnelling in Hebi colliery.The results show that the prediction for size-limited structures in the front of coal tunnelling is feasible using ANN.更多还原