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.


  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 723-732
  • Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility

Subject/Index Terms

Filing Info

  • Accession Number: 01868101
  • Record Type: Publication
  • ISBN: 9780784481523
  • Files: TRIS, ASCE
  • Created Date: Dec 21 2022 9:16AM