Deformation prediction model of concrete face rockfill dams based on an improved random forest model
作者机构：State Key Laboratory of Eco-hydraulics in Northwest Arid RegionXi'an University of TechnologyXi'an 710048China Power China Northwest Engineering Corporation LimitedXi'an 710065China
出 版 物：《Water Science and Engineering》 (水科学与水工程（英文版）)
年 卷 期：2023年第16卷第4期
页 面：390-398页
核心收录：
学科分类：081504[工学-水利水电工程] 08[工学] 0818[工学-地质资源与地质工程] 0903[农学-农业资源与环境] 0815[工学-水利工程] 0714[理学-统计学（可授理学、经济学学位）] 0814[工学-土木工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by the National Natural Science Foundation of China(Grant No.51979224) the China National Funds for Distinguished Young Scientists(Grant No.52125904)
主 题：Dam health monitoring M5'model tree IRF Monitoring models Settlement prediction
摘 要：The unique structure and complex deformation characteristics of concrete face rockfill dams(CFRDs)create safety monitoring *** study developed an improved random forest(IRF)model for dam health monitoring modeling by replacing the decision tree in the random forest(RF)model with a novel M5 model tree *** factors affecting dam deformation were preliminarily selected using the statistical model,and the grey relational degree theory was utilized to reduce the dimensions of model input ***,a deformation prediction model of CFRDs was established using the IRF *** ten-fold cross-validation method was used to quantitatively analyze the parameters affecting the IRF *** performance of the established model was verified using data from three specific measurement points on the Jishixia dam and compared with other dam deformation prediction *** point ES-10,the performance evaluation indices of the IRF model were superior to those of the M5 model tree and RF models and the classical support vector regression(SVR)and back propagation(BP)neural network models,indicating the satisfactory performance of the IRF *** IRF model also outperformed the SVR and BP models in settlement prediction at points ES2-8 and ES4-10,demonstrating its strong anti-interference and generalization *** study has developed a novel method for forecasting and analyzing dam settlements with practical ***,the established IRF model can also provide guidance for modeling health monitoring of other structures.
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