摘要
地应力、顶板岩性、巷道夹角、地下水及巷道断面积是影响巷道围岩稳定性的主要因素。文章利用RBF神经网络方法建立巷道围岩稳定性模型,结合呼和乌素煤矿的实测数据进行了验证,为该矿巷道进行有效支护提供了保障。
Angle between stress and the roadway, roof rock, and groundwater and basal area are the main factors which impact tunnel surrounding rock stability. Using RBF neural network to establish the rock mass stability model, combined with the measured data of the Huhewusu coal mine makes a verification, which provides assurance for the mine effective tunnel support.
出处
《煤》
2011年第9期16-18,共3页
Coal
关键词
围岩稳定性
RBF神经网络
模糊集合
评价方法
stability of surrounding rock
RBF neural network
fuzzy sets
evaluation methods
