摘要
根据软岩的力学及物理性质 ,分析了软岩巷道稳定性的影响因素 ,在此基础上应用神经网络理论建立了软岩巷道支护方式优化及巷道变形预测模型。模型在梅田矿务局的应用表明 :它能合理选择软岩巷道的支护方式 ,比较准确地预测巷道两帮和顶底板移近量 ;采用改进型BP算法 ,增加了网络的学习速度 ,加快了网络的收敛 ,提高了模型的精度。
On the basis of analysis of the factors influenci ng the stability of s oft rock roadway with different mechanical and physical features,a model to optimizing the support patterns of soft rock roadway and to pre dict its deformation is established by applying the theory of neural netwo rk. Its application in Meitian mining district shows that the model can select r ationally the support patterns of soft rock roadway and forecast accurately the deformation of sides and roof and floor of roadway, and that th e learning speed of network and the precision of model are enhanced with the app lication of reformatory BP algorithm.
出处
《岩土工程学报》
EI
CAS
CSCD
北大核心
2001年第6期708-710,共3页
Chinese Journal of Geotechnical Engineering
基金
广东省科研资助项目 (961 30 )
关键词
软岩巷道
支护方式
神经网络
巷道变形
预测模型
soft rock roadway
support pattern
neural network
optimization
prediction
