基于BP神经网络的多测点监测模型在大坝安全监测中的应用  

Multi-pointsmonitor model on BP neural network in the application of dam safety monitoring

作　　者：张国智[1,2] 陈建康[1,2] 张亦然 杨志勇[1,2] 潘望[1,2] ZHANG Guo-zhi;CHEN Jian-kang;ZHANG Yi-ran;YANG Zhi-yong;PAN Wang(School of Water Resources and Hydropower,Sichuan University,Chengdu 610065,China;State Key Laboratory of Hydraulics and Mountain River Engineering,Sichuan University,Chengdu 610065,China)

机构地区：[1]四川大学水利水电学院,成都610065 [2]水力学与山区河流开发保护国家重点实验室,成都610065

出　　处：《南水北调与水利科技》2015年第S01期216-219,共4页South-to-North Water Transfers and Water Science & Technology

摘　　要：建立了基于BP神经网络的多测点监测模型,为了验证该监测模型的有效性和精确性,通过具体的工程计算实例,将该模型的计算结果与统计回归单测点监测模型、BP神经网络单测点监测模型的计算结果比较。对比分析表明:对于TP8测值,统计回归模型平均误差为3.8%,BP神经网络单测点监测模型平均误差为9.4%,而BP神经网络的多测点监测模型平均误差仅为1.6%。因为BP神经网络的多测点监测模型考虑了各种效应量之间的相关性,预测结果比另外两种模型预测结果好,在大坝监测预测预报中具有一定的应用价值。This paper established a multi-pointsmonitor model on BP neural network for analysis of dam monitoring data,and contrast it with the traditional single-point regression model and single-point Model on BP neural network in a project.The results showed that the multi-pointmonitor model on BP neural network takes into account the correlation of various effects and the predicted results are better than the traditional single-point regression model and single-point model on BP neural network.So it has great value in the dam monitoring and prediction.

关 键 词：BP神经网络 安全监测 多测点监测模型 数据分析 

分 类 号：TV551.2[水利工程—水利水电工程]