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An understanding of human dynamics in urban subway traffic from the Maximum Entropy Principle

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  • Yong, Nuo
  • Ni, Shunjiang
  • Shen, Shifei
  • Ji, Xuewei

Abstract

We studied the distribution of entry time interval in Beijing subway traffic by analyzing the smart card transaction data, and then deduced the probability distribution function of entry time interval based on the Maximum Entropy Principle. Both theoretical derivation and data statistics indicated that the entry time interval obeys power-law distribution with an exponential cutoff. In addition, we pointed out the constraint conditions for the distribution form and discussed how the constraints affect the distribution function. It is speculated that for bursts and heavy tails in human dynamics, when the fitted power exponent is less than 1.0, it cannot be a pure power-law distribution, but with an exponential cutoff, which may be ignored in the previous studies.

Suggested Citation

  • Yong, Nuo & Ni, Shunjiang & Shen, Shifei & Ji, Xuewei, 2016. "An understanding of human dynamics in urban subway traffic from the Maximum Entropy Principle," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 222-227.
    • Handle: RePEc:eee:phsmap:v:456:y:2016:i:c:p:222-227
    DOI: 10.1016/j.physa.2016.03.071
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    References listed on IDEAS

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    Cited by:

    1. Yang, Kun & Ding, Yan & Zhu, Neng & Yang, Fan & Wang, Qiaochu, 2018. "Multi-criteria integrated evaluation of distributed energy system for community energy planning based on improved grey incidence approach: A case study in Tianjin," Applied Energy, Elsevier, vol. 229(C), pages 352-363.
    2. Yong, Nuo & Ni, Shunjiang & Shen, Shifei & Ji, Xuewei, 2020. "A study of fluctuations in subway traffic from the control properties of networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    3. Yang, Kun & Zhu, Neng & Chang, Chen & Wang, Daquan & Yang, Shan & Ma, Shengming, 2018. "A methodological concept for phase change material selection based on multi-criteria decision making (MCDM): A case study," Energy, Elsevier, vol. 165(PB), pages 1085-1096.

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