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根据８个指标（即岩石单轴抗压强度、岩石质量指标、岩石水稳性、地应力的最大主应力值、最大主应力方向与巷道走向夹角、巷道走向与岩层走向夹角、岩层倾角和巷道跨度），综合考虑生产矿井浅部巷道的工程经验和工程地质工作的超前性，提出基于人工神经网络的煤矿生产矿井延深巷道围岩工程地质分类方法，说明了该方法的基本原理，并结合实例说明了方法的实施与应用
According to the eight indicators (rock uniaxial compressive strength, rock quality index, rock water stability, the maximum principal stress value of the in-situ stress, the angle between the direction of the maximum principal stress and the direction of the roadway, the angle between the direction of the roadway and the strike of the strata, And roadway span), considering the engineering experience of shallow mine roadway and advancement of engineering geological work, this paper puts forward the engineering geological classification method of surrounding rock of mine roadway in coal mine production based on artificial neural network, explains the basic principle of this method, Combined with examples, it shows the implementation and application of the method