模糊聚类算法在道路状况分析中的应用研究

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1、Y821773中图分类号：TP391密级：单位代号：11903学号：02720633上海大学⑧硕士学位论文SHANGHAlUNIVERSITYMASTER，STHESIS题模糊聚类算法在道路状况目分析中的应用研究作者勾海波学科专业计算机应用导师欧阳为民完成日期2005年1月ABSTRACTWiththekeepingongrowingofurbantraffic，trafficproblemhasbeenaworld．wideproblemandurgesalmostallthecountriesspendlotsofmoneyandmanpoweron

2、thedevelopmentofIntelligentTransportationSystem(ITS)．AspartofITS，manycities，includesShangHai，haveequippedadvancedtrafficcontrolsystemSCATS，itcanrecordthetrafficdatawhilecontrolit．Howtofindusefulknowledgeinthesedatahasbeenaproblemthatneedstoberesolvedurgently．Becauseofthecharacter

3、isticsoftramcdata．traditionalwaysofdatamaintainandanalysisarenolongermeettheneedsoftrafficdataanalysis，however,datawarehouseanddataminingCandothejobwell．Datamining，whichisdefinedastheprocessofdiscoveringpatternsindata，isafocusofmultidisciplineresearch．Withtheuseofdatamining，wecan

4、dojobssuchasroadstateanalysis，predictionoftrafficiarnbaseonthetrafficdataefficiently．DatawarehouseiSadatasetwiththecharacteristicsofsubject-oriented，integrated，time—variantandnonvolatilewhichcanbeusedinsupportofdecisionsofadministrationdepartment．Therelationshipbetweendatamininga

5、nddatawarehouseareinterwovenandinter—developed．ThispaperconcentratesonfuzzyclusteringalgorithmFCManditsapplicationinroadstateanalysis．Afterintroducedbasicknowledgeofdatamininganddatawarehousebriefly，thispaperfirstdiscussedwaysoftrafficdatacollectionandfocusedonthecharacteristicof

6、trafficdata．ThenwediscussedthefuzzyclusteringalgorithmFCM．BecauseofthedisadvantageofFCMthatitslowspeedofconvergencecanleadtolowspeedofanalysis，proposedarefinedalgorithm：firstlyusestandardunittopartitionthedatasetandusetheaveragevalueofeachgridasinputtofeedtheFCMalgorithm；then，use

7、theclasslabelsofthevaluesasthelabeloftheoneswhichareinthesamegrid，astheseimprovementimplenaented，preferablyclusteringresultCanbegotwiththegreatimprovementofspeed．Thenweappliedtheimprovedalgorithmintheanalysisofroadstateanddiscussedtheresultofanalysiswhichisbasedonexperimentindept

8、h．FinallywediscussedthedesignofTrafficDa