Page 143 - 《水资源与水工程学报》2024年第2期
P. 143

!35 "!2 #                         & ' ( ) & * + , -                               Vol.35No.2
               2024 $ 4 %               JournalofWaterResources&WaterEngineering                 Apr.,2024

            DOI:10.11705/j.issn.1672-643X.2024.02.16


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                 GHIJK:TV139.1   LMNOP:A    LQRK:1672643X(2024)020139010

                   Intelligentinversionanalysisofgeologicalpermeabilitycoefficientsin
                                   hydraulicengineeringbasedonRF-GWO

                                                      2
                                        1
                                                                                        2
                                                                        1
                                LEIYan,WENLifeng,ZHAOMingcang,YINQiaogang
                     (1.PowerChinaNorthwestEngineeringCorporationLimited,Xi’an710065,China;2.StateKeyLaboratoryof
                      EcohydraulicsinNorthwestAridRegionofChina ,Xi’anUniversityofTechnology,Xi’an710048,China)
                 Abstract:Thegeologicalpermeabilitycoefficientsarethecrucialparametersforaccuratelyanalyzingthe
                 seepageinhydraulicengineering.Toaddresstheissuesoflowefficiencyandaccuracyofconventionalin
                 versionapproaches ,thisresearchutilizedacombinationofthefiniteelementforwardmodelandorthogonal
                 experimentaldesigntoconstructasamplesetforthepermeabilitycoefficientinversion.Then ,apermeabili
                 tycalculationsurrogatemodelbasedontherandomforest (RF)algorithmwasdeveloped.Subsequently,
                 thegreywolfoptimization(GWO)algorithm wasintroducedtodevelopanintelligentinversionmethod
                 basedonRF-GWO.TakingtheZpumpedstoragepowerstationasthecasestudy,itisfoundthatthewa
                 terlevelpredictionoutcomesoftheRFmodelarecloselyalignedwiththeactualmeasuredvaluesateach
                 borehole ,withtheperformancesurpassingCARTandBPmodels.Theoptimalgeologicalpermeabilitycoef
                 ficientcalculatedbyGWOperformsexcellentlyintheboreholewaterlevelinversion ,withamaximumrela
                 tiveerrorof0.42%,therebysatisfyingtherequiredaccuracyforengineeringapplications.Thecalculated
                 naturalseepagefielddistributionconformstothegeneraldistributionpatternsofmountainousseepage
                 fields.Therefore ,theproposedinversionmodelcanrapidlyandpreciselypredictthegeologicalpermeabili
                 tycoefficientintheprojectarea ,demonstratingsignificantengineeringpracticalityandvalue.
                 Keywords:geologicalpermeabilitycoefficient;inversionanalysis;orthogonalexperimentaldesign;ran
                 domforest(RF);greywolfoptimization(GWO)

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