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dc.contributor.author鄭群彥en_US
dc.contributor.authorCheng, Chun-Yenen_US
dc.contributor.author汪進財en_US
dc.contributor.authorWong, Jinn-Tsaien_US
dc.date.accessioned2014-12-12T02:43:21Z-
dc.date.available2014-12-12T02:43:21Z-
dc.date.issued2013en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT070053603en_US
dc.identifier.urihttp://hdl.handle.net/11536/75462-
dc.description.abstractCity-wide urban infrastructure are increasing reliant on information and communication technology (ICT) to improve and expand the service. Therefore, by taking advantage of passive sensors and Open Data policy, large scale of human behaviour data can be sensed and become more easily accessed independently. Data mining plays a vital role in helping to discover the patterns of human behaviour. In this study, we focus on the emerging urban transport infrastructure: public bikesharing system of Taipei City: YouBike. YouBike is launched from August 2012, operated by Giant, recognised as the world’s largest bicycle manufacturer. Besides, it was the first large-scale public bike sharing system to be implemented in Taiwan. Currently, there are 166 bike station is operation. This study has shown that how bikesharing usage data which mainly focuses on the changes of the number of available bicycles across all stations not only reveals the station activity patterns but also explores the underlying temporal and spatial dynamics of a city. The clustering results indicate that station activity patterns could be categorised into three groups: which are daytime origins nighttime destinations, daytime destinations nighttime origins, and combined origins and destinations. Each cluster groups reveal the different activity patterns throughout the day. We believe that the visualisation of average temporal activity patterns and the clustered results could easily lead to a better understanding of the bicycle availability information. In addition, it is expected to improve the Taipei YouBike service itself, avoiding a future empty or full station through an improved redistribution of bicycles via rebalancing trucks. As a result, it would help to improve user satisfaction with the enhanced service and it is possible to attract more people to use YouBike as an enhanced green transport system.zh_TW
dc.description.abstractCity-wide urban infrastructure are increasing reliant on information and communication technology (ICT) to improve and expand the service. Therefore, by taking advantage of passive sensors and Open Data policy, large scale of human behaviour data can be sensed and become more easily accessed independently. Data mining plays a vital role in helping to discover the patterns of human behaviour. In this study, we focus on the emerging urban transport infrastructure: public bikesharing system of Taipei City: YouBike. YouBike is launched from August 2012, operated by Giant, recognised as the world’s largest bicycle manufacturer. Besides, it was the first large-scale public bike sharing system to be implemented in Taiwan. Currently, there are 166 bike station is operation. This study has shown that how bikesharing usage data which mainly focuses on the changes of the number of available bicycles across all stations not only reveals the station activity patterns but also explores the underlying temporal and spatial dynamics of a city. The clustering results indicate that station activity patterns could be categorised into three groups: which are daytime origins nighttime destinations, daytime destinations nighttime origins, and combined origins and destinations. Each cluster groups reveal the different activity patterns throughout the day. We believe that the visualisation of average temporal activity patterns and the clustered results could easily lead to a better understanding of the bicycle availability information. In addition, it is expected to improve the Taipei YouBike service itself, avoiding a future empty or full station through an improved redistribution of bicycles via rebalancing trucks. As a result, it would help to improve user satisfaction with the enhanced service and it is possible to attract more people to use YouBike as an enhanced green transport system.en_US
dc.language.isoen_USen_US
dc.subject公共自行車租賃系統、使用型態、資料探勘、集群分析zh_TW
dc.subjectpublic bikesharing system, station activity pattern, data mining, cluster analysisen_US
dc.title台北公共自行車租賃系統使用型態之分析zh_TW
dc.titleBetter understanding the Taipei public bikesharing system: Exploring activity patternsen_US
dc.typeThesisen_US
dc.contributor.department運輸與物流管理學系zh_TW
Appears in Collections:Thesis


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