人民长江2024，Vol.55Issue(2)：231-237,7.DOI:10.16232/j.cnki.1001-4179.2024.02.030
基于改进随机森林的大坝监测数据质量评价算法
Data quality evaluation algorithm on dam monitoring based on improved random forest
摘要
Abstract
Aiming at the problems of low efficiency and insufficient intelligence of data quality evaluation in dam safety monito-ring,in order to meet the needs of real-time data quality evaluation of high-frequency automatic acquisition of dams,a quality evaluation criteria of safety monitoring data composed of six evaluation factors and related evaluation criteria from the four aspects of accuracy,integrity,timeliness and repair ability were proposed.And then a quality evaluation algorithm on historical data of dam safety monitoring was established by the improved random forest algorithm based on AUC value.The algorithm was applied to the evaluation of multi-year safety monitoring data of Liushugou concrete face rockfill dam in Xinjiang.The results showed that the random forest algorithm improved by AUC value was better than the original algorithm.When the feature attributes was 3,the effect was the best.The generalization error for the test set could reach 0.019 5,the average accuracy was stable at 96.97%,and the average accuracy of 10-fold cross validation reached 97.77%,which proved the feasibility of the new algorithm.关键词
大坝安全监测/数据质量评价/随机森林算法/评价因子Key words
dam safety monitoring/data quality evaluation/random forest algorithm/evaluation factor分类
建筑与水利引用本文复制引用
潘宇,李登华,丁勇..基于改进随机森林的大坝监测数据质量评价算法[J].人民长江,2024,55(2):231-237,7.基金项目
国家重点研发计划项目(2022YFC3005502) （2022YFC3005502）
国家自然科学基金项目(51979174) （51979174）
国家自然科学基金联合基金项目(U2040221) （U2040221）
中央级公益性科研院所基本科研业务费专项资金项目(Y321004) （Y321004）
