Page 128 - 《水资源与水工程学报》2022年第3期
P. 128
!33 " ! 3 # & ' ( ) & * + , - Vol.33No.3
2022 $ 6 % JournalofWaterResources&WaterEngineering Jun.,2022
DOI:10.11705/j.issn.1672-643X.2022.03.16
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8IBJK:TV641 LMNOP:A LQRK:1672643X(2022)03012408
Outlierdetectionandcorrectionforrollingspeedbasedon
Kmeans-EMDandIWOA-Elman
QIAOTiancheng,TONGDawei,WANGJiajun,GUANTao,WUBinping
(StateKeyLaboratoryofCivilEngineeringSimulationandSafety,TianjinUniversity,Tianjin300072,China)
Abstract:Rollingspeedisanimportantindicatorforevaluatingcompactionquality,butinthemonitoring
process,therollingspeediseasilydisturbedbyconstructionenvironment,positioningdriftandotherdis
turbances ,resultinginoutlierswhichwillaffecttheaccuracyofcompactionqualityevaluation.However,
methodsfordetectingandcorrectingoutliersofrollingspeedarenotreportedincurrentresearch.Toen
surethedataqualityoftherollingspeed ,basedonthecharacteristicsofthetimeseriesofrollingspeed,
weadoptedKmeansalgorithmtodetectoutlierspreliminarilyandweakentheinfluenceofoutliersonthe
resultsofempiricalmodedecomposition(EMD).AccordingtotheresultsofEMD,thefinequantitative
detectionofoutlierswasachieved ,whichinturnimprovedtheaccuracyofoutlierdetection.Further
more,whaleoptimizationalgorithm(WOA)improvedbychaospopulationinitialization,nonlinearcon
vergencefactors ,adaptiveinertialweightsandcatfisheffect-goldensinewasusedtooptimizetheElman
neuralnetworkandthenacorrectionmodelwasestablishedforthecorrectionofoutliersofrollingspeed.
AccordingtotheapplicationoftheproposedmethodtoalargehydropowerprojectinSouthwestChina,
thecombinedeffectofKmeansalgorithmandEMDcandetectoutliersofrollingspeedwithhigheraccura
cythantheboxplotmethod ;thecorrelationcoefficientbetweenthepredictedvalueoftheIWOA-Elman
neuralnetworkandtheactualvaluecanreachupto0.90775 ,comparedtoconventionalmodels,the
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