基于ACO-BP神经网络的大坝渗流监测应用研究  

Study on Dam Seepage Monitoring Application based on ACO-BP Neural Network

作　　者：王衣倩 宫丹丹 WANG Yi-qian;GONG Dan-dan(Heilongjiang Provincial Qingda Water Conservancy and Hydroelectric Power Limited Company,Harbin 150080,China??????????)

机构地区：[1]黑龙江省庆达水利水电工程有限公司

出　　处：《黑龙江水利科技》2019年第8期146-149,共4页Heilongjiang Hydraulic Science and Technology

摘　　要：随着我国水利工程的不断发展,施工环境复杂性和难度越来越高,坝体的安全监测内容十分重要,充分反应大坝实际安全稳定状态,降低施工风险。文章结合工程实例建立符合实际变形的ACO-BP神经网络预测模型,基于变形监测统计资料,定级预测坝体的渗流变形区间,通过计算成果分析该网络算法在大坝变形区间预测模型上能够实现设计要求。With continuous development of the water conservancy projects in China,the complexity and difficulty of construction environment is getting higher and higher,the safety monitoring contents of dam body is very important.The actual state of dam safety and stability is reflected fully to reduce the construction risk.Combined with a project case,ACO-BP neural network forecast model suitable for the actual deformation is established to predict the seepage deformation interval by grading based on the statistical data about deformation monitoring.The results show that this network algorithm can meet the design requirements in dam deformation interval prediction model through the analysis of calculation results.

关 键 词：大坝安全 监测 ACO-BP神经网络 渗流变形 

分 类 号：TV698.1[水利工程—水利水电工程]