南水北调与水利科技2016，Vol.14Issue(6)：116-121,158,7.DOI:10.13476/j.cnki.nsbdqk.2016.06.020
拱坝变形监测预报的随机森林模型及应用
Random forest model and application of arch dam′s deformation monitoring and prediction
摘要
Abstract
Dam deformation prediction plays an important role in the safety assessment of dam operation .Traditional models lack forecasting precision and the simulation effect is not stable enough .Besides ,if abnormal values of dam deformation exist ,tradi‐tional machine algorithm model lacks the flexibility of dealing with these abnormal data ,which will lead to the deviation of the forecasting results .In order to solve these problems ,random forest algorithm was introduced to the field of dam deformation monitoring for the first time .Similarity matrix of random forest was applied to divide dam deformation monitoring points into several parts .Random forests prediction model was established for each part ,which will avoid the defects of traditional models such as modeling of single point or using the same model for all deformation monitoring points .Establishing forecasting model for different parts of dam was more in line with engineering practice .Deformation data of one arch dam was analyzed and the feasibility of random forest model was verified .The results showed that partition of dam deformation points based on similarity matrix of random forest conformed to the physical and engineering practical significance .Compared with support vector machine and BP neural network model ,the prediction model of random forests for each part had the higher prediction precision and sta‐bility ,which provided a new approach in the area of dam safety monitoring .关键词
拱坝变形/监控模型/监测点分区/随机森林/变形预测Key words
arch dam deformation/monitoring model/partitions of monitoring points/random forests/deformation prediction分类
建筑与水利引用本文复制引用
罗浩,郭盛勇,包为民..拱坝变形监测预报的随机森林模型及应用[J].南水北调与水利科技,2016,14(6):116-121,158,7.基金项目
国家自然科学基金面上基金（51279057；41371048；40901015；51479062） FundNational Natural Science Foundation of China （）
