回采巷道围岩稳定性的神经网络控制

建立了煤矿回采巷道围岩分类与支护设计人工神经网络（ＢＰ网络）模型及巷道变形预测二级神经网络模型，并通过网络自适应、学习与匹配联想，得出了巷道围岩类别与支护强度及支护方式相对应的结果。同时，通过巷道变形预测二级神经网络模型预测了巷道顶底板移近速度，两帮移近速度及围岩动态。试验表明，神经网络（ＮＮ）输出结果与实际拟合良好。

Stability Control of Rocks Surrounding Gateways in Coal Mines by Using Neural Network

Abstract Artificial neural network methods are applied to two distinct aspects of stability control of rocks surrounding gateways in a coal mine.One is host rock classification and support selection by means of self adapting,learning and associating in BP(Back Propagation)algorithm.The other is prediction of the likely future deformations of gateways through two level neural network.And the network outputs are in a close agreement with the measured data.