基于熵权物元模型的北京地铁车站运营脆弱性评价分析

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1、万方数据ABSTRACTABSTRACT：WiththeadvanceofChina’Surbanizationprocess．thecontinuousimprovementofpeople’Slivingstandards，urbanpopulationisgrowing，trafficontheroads．EspeciallyinBeijingaSChina’Scapital．trafficcongestionproblemsaffectingpeople’Slives．Inordertoalleviatethegroundtrafficpr

2、essure，BeijingMetroisrapidlydeveloping．，dailylivesincreasingrelianceonsubway,passengerflowincreaserapidly．TheseresultinMetrooperationaccidentscontinuetooccur,subwaysafetyissuesgettheattentionoftheGovernmentandMetrooperationalcompany．Thus，bystudyingthevulnerabilityofsubwayopera

3、tion，reducethevulnerabilityofsubwaystationstoensurepersonnelsafetybecameaproblemtobesolved．Throughthestudyofliterature，wedefinethemeaningofoperationalvulnerabilityofsubwaystation，andestablishasubwaysystemvulnerabilityESARconceptmodel．Wedescribedegreeofexposure，sensitivity，adap

4、tabilityarethe3dimensionsofvulnerability，andexplaintherelationshipbetweenthese3dimensionsandvulnerability．StatisticalanalysisofBeijingMetroonehundredoperationalaccidents，combinedwithrelevanttheoryandrelatedvulnerabilityresearch，identifyingvulnerabilityfactors，thenwebuildtheeva

5、luationindexofBeringsubwayoperationalvulnerability．Applyentropymethod，acombinationweightingmethod，matter-elementtheoryandexpertconsultationmethodtocalculateindexweights．Establishingentropymatter-elementmodel，selectfourrepresentativestationsforvulnerabilityassessment，thenanalyz

6、eandresults．Throughtheoreticalanalysis，examplesshowthatentropymatter-elementmodeltotheapplicabilityofthevulnerabilityassessmentcarlbeusedinthesubwayoperation．BasedonthestatusquoofBeijingSubwayandevaluateresults，weproposedcountermeasurestoreducethevulnerabilityofsubwayforrefere

7、nce．KEYWORDS：vulnerability；conceptualmodel；entropy-matterelement；subwaystation；indexsystemCI．ASSNO：万方数据目录摘要⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．．vABSTRACT⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．vii1引言⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．11．1选题背景及意义⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．．11．1．1选题背景⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯

8、⋯⋯⋯⋯⋯11．1．2研究意义⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯21．2研究内容⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯