简介:Inordertoachievetheinformationfusioninthetimedomainbasedontheevidencetheory,anevidencecombinationmethodinthetimedomainbasedonreliabilityandimportanceisproposedaccordingtotheideaofevidencediscount.Firstly,thedistortionofthetime-domainevidenceisjudgedbasedonsingleexponentialsmoothing.Thereal-timereliabilityoftheevidenceattheadjacenttimeisobtainedbythereal-timereliabilityassessmentmethodoftheevidencebasedonthecredibilitydecaymodel.Then,therelativeimportanceoftheevidenceattheadjacenttimeisobtainedbycomprehensivelyconsideringimprovedconflictdegreeanduncertainty.Finally,basedonthecriterionofevidencediscountandtheDempster’sruleofcombination,theevidencecombinationiscarriedouttoachievethesequentialcombinationoftime-domainevidence.Thenumericalsimulationandanalysisshowthatthismethodhasfullyembodiedthedynamiccharacteristicsoftime-domainevidencecombination,andithasstrongprocessingabilityforconflictinformationandanti-disturbingability.Theproposedmethodhasgoodapplicabilitytoinformationfusioninthetimedomain.
简介:本单元知识网络同步讲解SectionA1.Whattimedoyougotoschool?你什么时候去上学?(1)whattime意为'什么时候,几点',常用来对具体的时间提问,可以用when替换。如:—WhattimedoesJimgotobed?吉姆什么时候睡觉?—Hegoestobedatteno’clock.他十点钟睡觉。
简介:Wehaveoptimizedtheinputpulsewidthandinjectiontimetoachievethehighestpossibleoutputpulseenergyinadouble-passlaseramplifierusingtwoNd:YAGrods.Forthispurpose,wehaveextendedtheFrantz–Nodvikequationbysimultaneouslyincludingbothspontaneousemissionandpumpenergyvariation.Theeffectivepumpenergyoftheflashlampwas8.84Jforeachgainmedium.Theenergyof1Jcouldbeamplifiedtoanoutputenergyof12.17Jwiththemaximumachievedextractionefficiencyof63.18%whenaninputpulsehavingapulsewidthof168μsissent10μsaftertheabsorbedpumpenergybecomesthemaximumvalue.
简介:Nonlinearwaveloadscaninducelow-frequencyandhigh-frequencyresonancemotionsofamooredplatformindeepwater.Fortheanalysisofthenonlinearresponseofanoffshoreplatformundertheactionofirregularwaves,themostwidelyusedmethodinpracticeistheCumminsmethod,inwhichthesecond-orderexcitingforcesinthetimedomainarecomputedbyatwo-termVolterraseriesmodelbasedonincidentwaves,first-orderbodymotionresponse,andquadratictransferfunctions(QTFs).QTFsarebichromaticwavesactingonabodyandarecomputedinthefrequencydomaininadvance.Formovingbodies,QTFsarerelatedtothefirst-orderbodyresponse,whichistobedeterminedinthesimulationprocessofbodymotionresponsebutisunknowninthecomputationprocedureofQTFs.Insolvingthisproblem,TengandCong(2017)proposedamethodtodividetheQTFsintodifferentcomponents,whichareunrelatedtothebodyresponse.WiththeapplicationofthenewQTFcomponents,amodifiedCumminsmethodcanbedevelopedforthesimulationofthenonlinearresponseofamooredfloatingplatform.Thispaperpresentsareviewofthetheory.
简介:Arobustcontrollerforbanktoturn(BTT)missileswithaerodynamicfinsandreactionjetcontrolsystem(RCS)isdevelopedbasedonnonlinearcontroldynamicmodelscomprisingcouplingsandaerodynamicuncertainties.Thefixedtimeconvergencetheoryisincorporatedwiththeslidingmodecontroltechniquetoensurethatthesystemtracksthedesiredcommandwithinuniformboundedtimeunderdifferentinitialconditions.Unlikepreviousterminalslidingmodeapproaches,theboundofsettlingtimeisindependentoftheinitialstate,whichmeansperformancemetricslikeconvergenceratecanbepredictedbeforehand.Toreducetheburdenofcontroldesignintermsofrobustness,extendedstateobserver(ESO)isintroducedforuncertaintyestimationwiththeoutputsubstitutedintothecontrollerasfeedforwardcompensation.Cascadecontrolstructureisemployedwiththeproposedcontrollawandthereinthecompoundcontrolsignalisobtained.Afterwards,controlinputsfortwokindsofactuatorsareallocatedonthebasisoftheirinherentcharacteristics.Finally,anumberofsimulationsarecarriedoutanddemonstratetheeffectivenessofthedesignedcontroller.
简介:Thewidespreadoflocation-basedsocialnetworksbringsaboutahugevolumeofusercheck-indata,whichfacilitatestherecommendationofpointsofinterest(POIs).Recentadvancesondistributedrepresentationshedlightonlearninglowdimensionaldensevectorstoalleviatethedatasparsityproblem.CurrentstudiesonrepresentationlearningforPOIrecommendationembedbothusersandPOIsinacommonlatentspace,andusers'preferenceisinferredbasedonthedistance/similaritybetweenauserandaPOI.SuchanapproachisnotinaccordancewiththesemanticsofusersandPOIsastheyareinherentlydifferentobjects.Inthispaper,wepresentanoveltranslation-based,timeandlocationaware(TransTL)representation,whichmodelsthespatialandtemporalinformationasarelationshipconnectingusersandPOIs.Ourmodelgeneralizestherecentadvancesinknowledgegraphembedding.Thebasicideaisthattheembeddingofa〈time,location〉paircorrespondstoatranslationfromembeddingsofuserstoPOIs.SincethePOIembeddingshouldbeclosetotheuserembeddingplustherelationshipvector,therecommendationcanbeperformedbyselectingthetop-kPOIssimilartothetranslatedPOI,whichareallofthesametypeofobjects.Weconductextensiveexperimentsontworeal-worlddata.sets.TheresultsdemonstratethatourTransTLmodelachievesthestate-of-the-artperformance.Itisalsomuchmorerobusttodatasparsitythanthebaselines.