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The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method

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DOI: 10.4236/jilsa.2013.54026    3,727 Downloads   5,309 Views   Citations

ABSTRACT

This paper studies the short-term prediction methods of sectional passenger flow, and selects BP neural network combined with the characteristics of sectional passenger flow itself. With a case study, we design three different schemes. We use Matlab to realize the prediction of the sectional passenger flow of the Beijing subway Line 2 and make comparative analysis. The empirical research shows that combining data characteristics of sectional passenger flow with the BP neural network have good prediction accuracy.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Q. Li, Y. Qin, Z. Wang, Z. Zhao, M. Zhan, Y. Liu and Z. Li, "The Research of Urban Rail Transit Sectional Passenger Flow Prediction Method," Journal of Intelligent Learning Systems and Applications, Vol. 5 No. 4, 2013, pp. 227-231. doi: 10.4236/jilsa.2013.54026.

References

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[3] R. Yang, “Study on Passenger Flow Forecast and Operation Scheduling Method of Urban Rail Transit,” Beijing Jiaotong University, Beijing, 2010.
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http://dx.doi.org/10.1038/323533a0
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