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软岩巷道支护方式优化的神经网络模型
引用本文:朱川曲,缪协兴,谢东海. 软岩巷道支护方式优化的神经网络模型[J]. 岩土工程学报, 2001, 23(6): 708-710
作者姓名:朱川曲  缪协兴  谢东海
作者单位:湘潭工学院资源工程系;中国矿业大学理学院;湘潭工学院资源工程系 湖南湘潭411201;江苏徐州221008;湖南湘潭411201;
基金项目:广东省科研资助项目(96130)
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。

关 键 词:软岩巷道  支护方式  神经网络  优化  预测  
文章编号:1000-4548(2001)06-0708-03
修稿时间:2001-03-13

A model for optimization of support patterns of soft rock roadway based on neural network
ZHU Chuanqu,MIAO Xiexing,XIE Donghai. A model for optimization of support patterns of soft rock roadway based on neural network[J]. Chinese Journal of Geotechnical Engineering, 2001, 23(6): 708-710
Authors:ZHU Chuanqu  MIAO Xiexing  XIE Donghai
Affiliation:1.Department of Resource Engineering Xiangtan Polytechnic University Xiangtan 411201 China 2.College of Science China University of Mining and Technology Xuzhou 221008 China
Abstract: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.
Keywords:soft rock roadway  support pattern  neural network  optimization  prediction
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