基于BP神经网络的隧洞围岩分类  

Classification of Tunnel Surrounding Rock Based on BP Neural Network

作　　者：甘海龙[1] GAN Hailong(Guangxi Technological College of Machinery and Electricity,Nanning,Guangxi,530007)

机构地区：[1]广西机电职业技术学院,广西南宁530007

出　　处：《红水河》2021年第4期122-125,134,共5页Hongshui River

基　　金：2017年度广西高校中青年教师科研基础能力提升项目(2017KY075)。

摘　　要：为了检验BP神经网络在隧洞围岩分类中的可行性,利用BP神经网络模式识别的特性,构建了隧洞围岩分类的神经网络模型。以30组实测数据作为神经网络的学习样本,7组实测数据验证神经网络的工作性能,BP神经网络输出的分类结果与实际的分类结果完全一致,表明训练良好的BP神经网络可以用于工程实践中的隧洞围岩分类。In order to test the feasibility of BP neural network in tunnel surrounding rock classification,the neural network model of tunnel surrounding rock classification is constructed by using the characteristics of BP neural network pattern recognition.Taking 30 groups of measured data as the learning samples of neural network,7 groups of measured data verify the working performance of neural network.The classification results of BP neural network output are completely consistent with the actual classification results,which shows that the trained BP neural network can be used for the classification of tunnel surrounding rock in engineering practice.

关 键 词：隧洞 围岩 分类 BP神经网络 

分 类 号：U452.12[建筑科学—桥梁与隧道工程] TP183[交通运输工程—道路与铁道工程]