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題名 臺北市公共自行車站點需求分析之研究
A research in the demand of the public bike station in Taipei.
作者 張辰尉
貢獻者 白仁德
張辰尉
關鍵詞 大數據
公共自行車系統
微笑單車
社群網絡分析
熱點分析
最小平方法
地理加權迴歸
Big data
Public bike system
Youbike
Social network analysis
Hot spot analysis
Least squares method
Geographically weight regression
日期 2017
上傳時間 31-Aug-2017 12:20:07 (UTC+8)
摘要 近年來由於溫室效應加劇以及氣候變遷加劇，因此符合綠色運輸特性的公共自行車系統，成為各國交通部門發展綠運輸政策時的目標之一，同時，大數據分析亦是目前受到高度關注的熱門議題。而本研究首先使用臺北市微笑單車租借大數據探討在不同時間點下民眾日常使用微笑單車之旅運行為，分析不同站點間的旅次特性。再運用社群網絡分析，以站點之間旅次連結多寡作為權重，探討站點間之緊密程度，以及不同時間點下微笑單車租借量之熱點分布情形，並將其視覺化呈現。
後續透過文獻分析，擷取影響公共自行車使用量之因素後，本研究嘗試運用一般線性迴歸模型與地理加權迴歸進行模型建立，並探討各影響因素對於旅運需求之影響情形。實證結果顯示，地理加權迴歸模型可以解決一般線性迴歸所產生空間自相關問題，使得模型解釋能力獲得改善。本研究並使用地理加權迴歸進行使用需求分析以及預測，對未來公共自行車營運以及站點擴張提出結論以及建議，期能提升公共自行車系統之使用量。
Due to the climate change and aggravation of the greenhouse effect in recent years, the public bicycle system with the feature of low-carbon emission has raised more and more attention internationally, and has become one of the targets in developing green transportation policies of transportation departments of governments around the world. Meanwhile Big Data analysis issues, on the other hand, are currently a sought-after topic which has caused great concern as well. In this study, we utilize the rental data of the YouBike system in Taipei to discuss the public usage of YouBike tour at different periods. With the use of social network analysis, we discuss the relationships between different bicycle stops based on applying the number of travels between different sites as the weight. Eventually, the hotspot analysis will be carried out by operating the GIS system. In this way, we are able to discuss the hotspot distribution of YouBike rentals in different time and then visualize the result.
After that this study pick up the variables which will effect the YouBike usage by reference review. This research try to built models by utilizing the Least Squares Method and Geographically Weighted Regression. Then we will have a discussion with the result of the two models. The result shows that Geographically Weighted Regression can resolve the spatial autocorrelation problem which happened in the Least Squares Method and to gain a better result. With the analysis and prediction of public bicycle system from Geographically Weighted Regression, we hope to raise the usage of public bicycle system by concluding as well as making recommendations for the future operation of public bicycle and the expansion of bicycle stops.
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交通部運輸研究所，2012，交通政策白皮書，交通部運輸研究所。

臺北市交通局，2015，105年公共自行車租賃站設置準則訂彈性作業方式 ，台北市政府交通局。

白詩滎，2013，臺北公共自行車使用行為特性分析與友善環境建構之研究，國立政治大學碩士學位論文。

王俊偉，2011，以系統模擬探討公共自行車租借系統之建置及營運策略，國立成功大學資訊管理研究所碩士論文。

邱辰，2015，從空間角度分析公共自行車系統對站點周邊土地活動影響，國立臺灣大學碩士學位論文。

余書枚，2009，公共自行車租借系統選擇行為之研究，國立交通大學交通運輸研究所碩士學位論文。

曹壽民、林俊宏，2004，臺北都會區捷運車站腳踏車停車需求之研究，『都市交通季刊』19(3)：16-31。

李家儂、賴宗裕，2009，交通運輸與土地使用連結下的都市模式演變-全球36個主要城市比較分析，『都市與計劃』36(1)：25-49。

鄭雨桐，2016，建成環境對公共自行車使用之影響，國立臺灣大學地理環境資源學系研究所碩士學位論文。

王勇、靳瑞濤、蘇煜釗、陳春禮，2016，網絡大數據時代的發展現狀與挑戰，『農業經濟』(4)：21-24。

詹佳俊，2015，向塞車問題宣戰!荷蘭TNO將與Google合作分析交通大數據，數位時代，11月22日。

李永正，2015，如何在大數據時代發揮開放資料的社會價值，『台灣經濟研究月刊』38(9)：105-112

于嘉元，2009，土地使用變遷之空間自迴歸分析-以新店安坑地區為例，國立台灣大學建築與城鄉研究所碩士學位論文。

程稚茵，2016，用地理加權迴歸分析獨立式與集合式住宅之價格分布-已改制前台中市為例，國立政治大學地政學系碩士學位論文。

陳慈仁，2001，台北市資訊軟體業與網際網路服務業區位分佈之研究，國立台灣大學建築與城鄉研究所碩士學位論文。

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描述 碩士
國立政治大學
地政學系
104257010
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0104257010
資料類型 thesis
dc.contributor.advisor 白仁德zh_TW
dc.contributor.author (Authors) 張辰尉zh_TW
dc.creator (作者) 張辰尉zh_TW
dc.date (日期) 2017en_US
dc.date.accessioned 31-Aug-2017 12:20:07 (UTC+8)-
dc.date.available 31-Aug-2017 12:20:07 (UTC+8)-
dc.date.issued (上傳時間) 31-Aug-2017 12:20:07 (UTC+8)-
dc.identifier (Other Identifiers) G0104257010en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/112404-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 地政學系zh_TW
dc.description (描述) 104257010zh_TW
dc.description.abstract (摘要) 近年來由於溫室效應加劇以及氣候變遷加劇，因此符合綠色運輸特性的公共自行車系統，成為各國交通部門發展綠運輸政策時的目標之一，同時，大數據分析亦是目前受到高度關注的熱門議題。而本研究首先使用臺北市微笑單車租借大數據探討在不同時間點下民眾日常使用微笑單車之旅運行為，分析不同站點間的旅次特性。再運用社群網絡分析，以站點之間旅次連結多寡作為權重，探討站點間之緊密程度，以及不同時間點下微笑單車租借量之熱點分布情形，並將其視覺化呈現。
後續透過文獻分析，擷取影響公共自行車使用量之因素後，本研究嘗試運用一般線性迴歸模型與地理加權迴歸進行模型建立，並探討各影響因素對於旅運需求之影響情形。實證結果顯示，地理加權迴歸模型可以解決一般線性迴歸所產生空間自相關問題，使得模型解釋能力獲得改善。本研究並使用地理加權迴歸進行使用需求分析以及預測，對未來公共自行車營運以及站點擴張提出結論以及建議，期能提升公共自行車系統之使用量。		zh_TW
dc.description.abstract (摘要) Due to the climate change and aggravation of the greenhouse effect in recent years, the public bicycle system with the feature of low-carbon emission has raised more and more attention internationally, and has become one of the targets in developing green transportation policies of transportation departments of governments around the world. Meanwhile Big Data analysis issues, on the other hand, are currently a sought-after topic which has caused great concern as well. In this study, we utilize the rental data of the YouBike system in Taipei to discuss the public usage of YouBike tour at different periods. With the use of social network analysis, we discuss the relationships between different bicycle stops based on applying the number of travels between different sites as the weight. Eventually, the hotspot analysis will be carried out by operating the GIS system. In this way, we are able to discuss the hotspot distribution of YouBike rentals in different time and then visualize the result.
After that this study pick up the variables which will effect the YouBike usage by reference review. This research try to built models by utilizing the Least Squares Method and Geographically Weighted Regression. Then we will have a discussion with the result of the two models. The result shows that Geographically Weighted Regression can resolve the spatial autocorrelation problem which happened in the Least Squares Method and to gain a better result. With the analysis and prediction of public bicycle system from Geographically Weighted Regression, we hope to raise the usage of public bicycle system by concluding as well as making recommendations for the future operation of public bicycle and the expansion of bicycle stops.		en_US
dc.description.tableofcontents 第一章 緒論 1
第一節 研究動機與目的 1
第二節 研究範疇 6
第三節 研究方法 7
第四節 研究內容與流程 8
第二章 文獻回顧與理論基礎 11
第一節 公共自行車系統界定 11
第二節 影響公共自行車使用之相關研究 21
第三節 空間統計理論 33
第三章 研究設計 39
第一節 來源資料說明與處理 39
第二節 研究架構 45
第三節 投入變數說明 47
第四章 實證分析結果 53
第一節 微笑單車使用量空間分析 53
第二節 線性迴歸分析結果 59
第三節 地理加權迴歸分析結果 74
第四節 一般線性迴歸與地理加權迴歸比較與分析 89
第五章 結論與建議 95
第一節 結論 95
第二節 後續研究建議 97
參考文獻 99		zh_TW
dc.format.extent 10645898 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0104257010en_US
dc.subject (關鍵詞) 大數據zh_TW
dc.subject (關鍵詞) 公共自行車系統zh_TW
dc.subject (關鍵詞) 微笑單車zh_TW
dc.subject (關鍵詞) 社群網絡分析zh_TW
dc.subject (關鍵詞) 熱點分析zh_TW
dc.subject (關鍵詞) 最小平方法zh_TW
dc.subject (關鍵詞) 地理加權迴歸zh_TW
dc.subject (關鍵詞) Big dataen_US
dc.subject (關鍵詞) Public bike systemen_US
dc.subject (關鍵詞) Youbikeen_US
dc.subject (關鍵詞) Social network analysisen_US
dc.subject (關鍵詞) Hot spot analysisen_US
dc.subject (關鍵詞) Least squares methoden_US
dc.subject (關鍵詞) Geographically weight regressionen_US
dc.title (題名) 臺北市公共自行車站點需求分析之研究zh_TW
dc.title (題名) A research in the demand of the public bike station in Taipei.en_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 許添本，2003，人本交通與綠色交通的發展理念，『都市交通季刊』18(3)：41-52。

交通部運輸研究所，2012，交通政策白皮書，交通部運輸研究所。

臺北市交通局，2015，105年公共自行車租賃站設置準則訂彈性作業方式 ，台北市政府交通局。

白詩滎，2013，臺北公共自行車使用行為特性分析與友善環境建構之研究，國立政治大學碩士學位論文。

王俊偉，2011，以系統模擬探討公共自行車租借系統之建置及營運策略，國立成功大學資訊管理研究所碩士論文。

邱辰，2015，從空間角度分析公共自行車系統對站點周邊土地活動影響，國立臺灣大學碩士學位論文。

余書枚，2009，公共自行車租借系統選擇行為之研究，國立交通大學交通運輸研究所碩士學位論文。

曹壽民、林俊宏，2004，臺北都會區捷運車站腳踏車停車需求之研究，『都市交通季刊』19(3)：16-31。

李家儂、賴宗裕，2009，交通運輸與土地使用連結下的都市模式演變-全球36個主要城市比較分析，『都市與計劃』36(1)：25-49。

鄭雨桐，2016，建成環境對公共自行車使用之影響，國立臺灣大學地理環境資源學系研究所碩士學位論文。

王勇、靳瑞濤、蘇煜釗、陳春禮，2016，網絡大數據時代的發展現狀與挑戰，『農業經濟』(4)：21-24。

詹佳俊，2015，向塞車問題宣戰!荷蘭TNO將與Google合作分析交通大數據，數位時代，11月22日。

李永正，2015，如何在大數據時代發揮開放資料的社會價值，『台灣經濟研究月刊』38(9)：105-112

于嘉元，2009，土地使用變遷之空間自迴歸分析-以新店安坑地區為例，國立台灣大學建築與城鄉研究所碩士學位論文。

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