简介：Three-dimensionelectronicchartdisplayinformationsystem(ECDIS)isoneofthenewdevelopingdirectionsofelectronicnavigationchart,anditsreal-timequalityisoneoftheimportantrequirements.Inthispaperthealgorithmofsimplifyingtrianglesurfaceusingedgecontraction,whichcanensurethereal-timedisplayofobjectsinseabedenvironment,wasputforward.TheoptimumcontractionpointwasdeterminedbytheLagrangematrix,sothatthealgorithmensuresthatthecontractionpointlocatesontheoriginalmodel,meanwhilemeetsthedemandsofleastdeviation.Thisalgorithmcanimprovetheplottingspeed,andpreservetheboundarycharacterbyusingthefewertrianglestosimulateobjects.

简介：Itisverydifficulttoestimateexactvaluesoftimeandcostofanactivityinprojectschedulingprocessbecausemanyuncertainfactors,suchasweather,productivitylevel,humanfactorsetc.,dynamicallyaffectthemduringprojectimplementationprocess.AGAs-basedfullyfuzzyoptimaltime-costtrade-offmodelispresentedbasedonfuzzysetsandgeneticalgorithms(GAs).Intihsmodelallparametersandvariablesarecharacteristicsbyfuzzynumbers.AndthenGAsisadoptedtosearchfortheoptimalsolutiontothismodel.Themethodsolvesthetime-costtrade-offproblemsunderanuncertainenvironmentandisprovedpracticablethroughagivingexampleinshipbuildingscheduling.

简介：ADRNN(diagonalrecurrentneuralnetwork)anditsRPE(recurrentpredictionerror)learningalgorithmareproposedinthispaper.UsingofthesimplestructureofDRNNcanreducethecapacityofcalculation.TheprincipleofRPElearningalgorithmistoadjustweightsalongthedirectionofGauss-Newton.Meanwhile,itisunnecessarytocalculatethesecondlocalderivativeandtheinversematrixes,whoseunbiasednessisproved.Withapplicationtotheextremelyshorttimepredictionoflargeshippitch,satisfactoryresultsareobtained.Predictioneffectofthisalgorithmiscomparedwiththatofauto-regressionandperiodicaldiagrammethod,andcomparisonresultsshowthattheproposedalgorithmisfeasible.