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dc.contributor.authorChen, Mu-Chenen_US
dc.contributor.authorChen, Long-Shengen_US
dc.contributor.authorWei, Yuen_US
dc.date.accessioned2018-08-21T05:56:46Z-
dc.date.available2018-08-21T05:56:46Z-
dc.date.issued2017-01-01en_US
dc.identifier.urihttp://hdl.handle.net/11536/146627-
dc.description.abstractThis paper applies both Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD) to extract the EMD and EEMD components from a data set of passenger flows of a station in the metro system, and illustrates the time variants of short-term passenger flow for this data sets. The results indicate that the extracted meaningful EEMD components reveal a more unique pattern than the extracted meaningful EMD components. The patterns of these EEMD components of passenger flow in the metro system are more specific and can be explained more easily for management purposes.en_US
dc.language.isoen_USen_US
dc.subjectensemble empirical mode decompositionen_US
dc.subjecthilbert-huang transformen_US
dc.subjectpassenger flowen_US
dc.subjecttime varianten_US
dc.subjectmetro stationen_US
dc.titleApply Ensemble Empirical Mode Decomposition to Discover Time Variants of Metro Station Passenger Flowen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2017 4TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND APPLICATIONS (ICIEA)en_US
dc.citation.spage239en_US
dc.citation.epage243en_US
dc.contributor.department運輸與物流管理系 註:原交通所+運管所zh_TW
dc.contributor.departmentDepartment of Transportation and Logistics Managementen_US
dc.identifier.wosnumberWOS:000403392200048en_US
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