User behavior analysis based on shared bike trip data

  • HAN Zhen ,
  • YANG Li ,
  • XU Xiao-fan
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  • (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

Received date: 2019-03-18

  Revised date: 2019-06-21

  Online published: 2019-06-21

Abstract

Based on the shared bicycle travel data, the overall travel time and intensity of users were analyzed, and the travel dates and routes of  high frequency users  were classified accordingly,and  a prediction model was established for users' travel destinations.The results show that there are significant differences in travel time distribution between weekdays and weekends, and travel intensity has the characteristics of low frequency and short distance;the travel trajectory of high frequency users can be classified into three types in two dimensions of work and leisure;the accuracy rate of the proposed user travel destination prediction model is more reasonable based on the shared bicycle travel data.

Cite this article

HAN Zhen , YANG Li , XU Xiao-fan . User behavior analysis based on shared bike trip data[J]. Journal of Dalian Maritime University, 2019 , 45(4) : 80 -86 . DOI: 10.16411/j.cnki.issn1006-7736.2019.04.011

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