Apply Ensemble Empirical Mode Decomposition to Discover Time Variants of Metro Station Passenger Flow
| dc.citation.epage | 243 | en_US |
| dc.citation.spage | 239 | en_US |
| dc.contributor.author | Chen, Mu-Chen | en_US |
| dc.contributor.author | Chen, Long-Sheng | en_US |
| dc.contributor.author | Wei, Yu | en_US |
| dc.contributor.department | 運輸與物流管理系 註:原交通所+運管所 | zh_TW |
| dc.contributor.department | Department of Transportation and Logistics Management | en_US |
| dc.date.accessioned | 2018-08-21T05:56:46Z | |
| dc.date.available | 2018-08-21T05:56:46Z | |
| dc.date.issued | 2017-01-01 | en_US |
| dc.description.abstract | This 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.identifier.journal | 2017 4TH INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND APPLICATIONS (ICIEA) | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/146627 | |
| dc.identifier.wosnumber | WOS:000403392200048 | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | ensemble empirical mode decomposition | en_US |
| dc.subject | hilbert-huang transform | en_US |
| dc.subject | passenger flow | en_US |
| dc.subject | time variant | en_US |
| dc.subject | metro station | en_US |
| dc.title | Apply Ensemble Empirical Mode Decomposition to Discover Time Variants of Metro Station Passenger Flow | en_US |
| dc.type | Proceedings Paper | en_US |
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