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1、武汉理工大学硕士学位论文AbstractIntheageoftheelectroniccommerce,theelectroniccommerce,logisticsindustry,logisticsvehiclesaremoreprosperitythanever.MoreandmorelogisticsvehiclesGPSdataareproduced.Thesedatacontainalotoftrafficinformationsuchasroadconditions,vehicles,andevensocialandeconomicdevelopment.Throughsta
2、tisticsandanalysisofvehicledrivingdistance,time,location,vehicleparkingcharacteristics,trajectorydataminingcanfindshippinglinecharacteristics,providelogisticscompanybasedonvehicleschedulingschemessuchastime,cost,andderivedaseriesofLBSapplication.TakingmassiveGPSdataasthedatasource,usingmassivetraj
3、ectorydataminingandrelatedtheoryofroadrecommending,composedbyonlineandofflinesystem,thispaperproposesandrealizesadesignframeworkofrouterecommendingsystemforlogisticsvehiclethroughestablishingclusteringmodelandanalyzingmassiveGPSdatatounderstandthedrivingruleoflogisticsvehicles.Thekeyapproachisdeep
4、studyingondatapreprocessing,stopsdetecting,routesegmenting,similarfreighttrajectoryclusteringandfreightlinesrecommending.Thespecificworkisasfollows:Asanecessaryworkintrajectorydatamining，istudythepretreatmentmethod,includingdatacleaning,dataofabnormaldetectionandexclusion,andwiththecharacteristics
5、ofthissystemalltheGPSdatainanalysisandputforwardakindofanomalydetectionalgorithmbasedonthehistoricaltrajectorydata.Thealgorithmformassivedataprocessinghaslowtimecomplexity.Parkingpointsdetectionandpathintegralcanfindthatthepatternoflogisticsvehiclesandgoods.Inthispaper,onthebasisofnaivebayesalgori
6、thm,iputforwardanewwayfortrajectorysegmentation,accordingtothelogisticsvehicleparkingandordinaryponitsusingthedifferentattributesoftimeandspacebetweenthemwhengoodsareloadedandunloaded.Iregulatefreighttrajectoriesclusteringsimilartothesamestartingpointandendpointofthetrajectory.thenprojectthemonthe
7、samelatitude.Afterthatusingk-meansalgorithm,thecharacteristicoftrajectoryisanalyzed,andfinallygetII万方数据武汉理工大学硕士学位论文logisticsvehiclegeneralmovementtracks.Intherecommendationofshippinglines,basedonthedifferenceofhi
