Study on Prediction Method of Bicycle Passenger Flow Based on Data Information of Mobike
Using computer data mining and analysis, the authors present data of Mobike within a study area in Xi’an. A typical interval of peak value is divided by the method of Fisher sequence clustering and based on the statistics data of Mobike in the study region. With the typical characteristics of the peak interval, a pertinent investigation of Mobike bicycle flow and total of cycling passenger flow is carried out. Data samples of actual passenger flow were obtained from a survey. By combining the real-time data of Mobike with passenger flow data, a regression equation is established for predicting total bicycle passenger flow under different peak passenger flows of Mobike to predict total bicycle passenger flow of short distances in the study region over different periods.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
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Supplemental Notes:
- © 2018 American Society of Civil Engineers.
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Peng, Hui
- Zhang, Na
- Zheng, Jinnan
- Yu, Jingcai
- Ding, Tian
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Conference:
- 18th COTA International Conference of Transportation Professionals
- Location: Beijing , China
- Date: 2018-7-5 to 2018-7-8
- Publication Date: 2018-7
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 723-732
- Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility
Subject/Index Terms
- TRT Terms: Bicycles; Data mining; Forecasting; Traffic flow
- Identifier Terms: Mobike
- Geographic Terms: Xi'an (China)
- Subject Areas: Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting;
Filing Info
- Accession Number: 01868101
- Record Type: Publication
- ISBN: 9780784481523
- Files: TRIS, ASCE
- Created Date: Dec 21 2022 9:16AM