Research of State Vector in Short-Term Passengers Flow Forecasting Based on Nonparametric Regression

Authors

Guo Han, School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China;
Pengpeng Jiao, School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China;

Abstract

Abstract: KNNR (K Nearest Neighbor Based Nonparametric Regression) Method was used for short-term traffic forecast and the choice of state vector was studied. The result shows that taking the data of some historical periods as the state vector has a good prediction. Although the correlation of the historical passenger flow between different Rail transit sites is significant, it neglects the fact that the passengers enter each station is independent. So taking the historical passenger flow of adjacent sites as the state vector is not appropriate.

Recommended Citation

Han, Guo and Jiao, Pengpeng (2020) "Research of State Vector in Short-Term Passengers Flow Forecasting Based on Nonparametric Regression," Journal of System Simulation: Vol. 29: Iss. 9, Article 34.
DOI: 10.16182/j.issn1004731x.joss.201709034
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss9/34

First Page

2128

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201709034

Last Page

2134

CLC

U491

Recommended Citation

Guo Han, Jiao Pengpeng. Research of State Vector in Short-Term Passengers Flow Forecasting Based on Nonparametric Regression[J]. Journal of System Simulation, 2017, 29(9): 2128-2134.

DOI

10.16182/j.issn1004731x.joss.201709034