Page 48 - 2023年第54卷第6期
P. 48

[21] ZHAOXJ,JIAY,LIAP,etal.Multi - sourceknowledgefusion:asurvey[J].WorldWideWeb - Internetand
                       WebInformationSystems ,2020,23(4):2567 - 2592.
                [22] ZOUL,ZSUM T.Graph - basedRDFdatamanagement[J].DataScienceandEngineering,2017,2:56 - 70.
                [23] WYLOTM,HAUSWIRTH M,CUDRE - MAUROUXP,etal.RDFdatastorageandQueryProcessingSchemes:
                       Asurvey[J].ACM ComputingSurveys,2019,51(4):1 - 36.
                [24] RAULF.Extractingcompanynamesfrom text[C]??Proceedingsofthe7thIEEEConferenceonArtificialIntelli
                       genceApplications,1991.
                [25] LIUX,ZHANG S,WEIF,etal.Recognizingnamedentitiesintweets[C]??Proceedingsofthe49thAnnual
                       MeetingoftheAssociationforComputationalLinguistics ,2011.
                [26] HUANGZH,XUW,YUK.BidirectionalLSTM- CRFmodelsforsequencetagging[EB?OL].(2015 - 08 - 09)
                       [ 2022 - 10 - 16].https:??arxiv.org?pdf?1508.01991v1.pdf.
                [27] DEVLINJ,CHANGM W,LEEK,etal.BERT:Pretrainingofdeepbidirectionaltransformersforlanguageun
                       derstanding [EB?OL].(2019 - 05 - 24)[2022 - 10 - 17].https:??arxiv.org?pdf?1810.04805.pdf.
                [28] 李晓庆,唐昊,司加胜,等.面向混合属性数据集的改进半监督 FCM 聚类方法[J].自动化学报,2018,
                      44(12):2259 - 2268.
                [29] MIKOLOVT,CHENK,DEAN J,etal.Efficientestimationofwordrepresentationsinvectorspace[EB?OL].
                       (2013 - 09 - 27)[2022 - 10 - 17].https:??arxiv.org?pdf?1301.3781v3.pdf.
                [30] 官赛萍,靳小龙,贾岩涛,等.面向知识图谱的知识推理研究进展[J].软件学报,2018(10):2966 - 2994.
                [31] CHENY,GOLDBERGS,WANGDZ,etal.Ontologicalpathfinding:miningfirst - orderknowledgefrom large
                       knowledgebases [C]??Proceedingsof2016InternationalConferenceonManagementofData,2016.



                 Aknowledge - drivenapproachforintelligentgenerationofhydraulicengineeringcontingency
                    plans:AcasestudyoftheMiddleRouteofSouth - to - NorthWaterDiversionProject

                                                    1
                                     1,2
                                                               3
                                                                               4
                           LIUXuemei ,LUHankang,LIHairui,HUAIXianfeng,CHENXiaolu             4
                  (1.SchoolofInformationEngineering,NorthChinaUniversityofWaterResourcesandElectricPower,Zhengzhou 450000,China;
                          2.CollaborativeInnovationCenterforEfficientUtilizationofWaterResources,Zhengzhou 450000,China;
                 3.SchoolofManagementandEconomics,NorthChinaUniversityofWaterResourcesandElectricPower,Zhengzhou 450000,China;
                             4.ChinaSouth - to - NorthWaterDiversionGroupMiddleLineCo.,Ltd,Beijing 100038,China)

                  Abstract:Traditionalemergencyplansforhydraulicengineeringprojectshaveproblemssuchaslowdigitisation,
                  poorcontentrelevanceandinsufficientintelligentaidfordecision - making.Inthispaper,weusetheknowledge
                  graphanddeeplearningtechnologytocreateanintelligentgenerationmodelofemergencyplansforhydraulicengi
                  neeringprojects.Firstly ,basedonthetextofriskpreventionandcontrolmanualandtheemergencyplan,wepro
                  poseaknowledgegraphontologymodelofemergencyplan ,constructaknowledgegraphofemergencyplan,and
                  realisethestructuredexpressionofnon - structuralinformationinthetextofemergencyplan.Secondly,basedon
                  thewaterresourcesengineeringinspectiontext ,weuseBERT(Bi - directionalEncoderRepresentationfromTrans
                  formers )+BiLSTM +CRF(Bi - directionalLongShortTermMemorywithConditionalRandomFields)entityrec
                  ognitionmodeltointelligentlyidentifyriskevents ,projectsandotherentitiesintheinspectiontext.Finally,anin
                  telligentgenerationtemplateforemergencysolutionsisdesigned ,andthroughmulti - featurefusionofentityalign
                  menttechnology , knowledge retrievaland inference technology, the intelligentgeneration and pushing of
                  emergencysolutionsisrealised.Throughthemodelaccuracyanalysisandthevalidationofexamplessuchas“chan
                  nelleakage ”,thispapershowsahighrecognitionaccuracy(F1valueof96.21%)andareliableemergencyplan
                  generation,whichcanbeextendedtoemergencymanagementsuchasemergencyrescueofhydraulicengineering
                  projectsandintelligentgenerationofemergencyplans.
                  Keywords:knowledgegraph;hydraulicengineering;emergencyplan;South - to - NorthWaterDiversion


                                                                                    (责任编辑:于福亮)


                —  6 7  —
                     6
   43   44   45   46   47   48   49   50   51   52   53