Comparison and Application of Imputation Methods for Temporal Data in Surface Water Quality Monitoring
The integrity and accuracy of national surface water quality monitoring data are of great significance for safeguarding public health,protecting ecological environment and supporting water resources management.Comparative analysis of the applicability and effectiveness of nine methods including two kinds of single imputation(Mean Imputation and KNN)and seven kinds of multiple imputation methods(MF,MICE,blasso,norm,norm.boot,norm.nob,ri)in surface water quality monitoring data.The imputation methods performance of 7 surface water quality indicators in Tumenlou section of Beiyun River,Wuqing District,Tianjin from 2020 to 2022 was evaluated by above 9 imputation methods,and the actual missing data of the same indicators were analyzed empirically.The results showed that the blasso multiple imputation method produced superior imputation results.It maximizes the utilization of auxiliary variables and prior information of various indicators to improve imputation accuracy.Additionally,Bayesian Lasso has a fast convergence speed and controllable imputation time.
万方数据
维普
