A New Phase Space Reconstruction Method for Prediction of Public Transit Passenger Volume

DOI

10.2991/isrme-15.2015.220How to use a DOI?

Keywords

phase space reconstruction; support vector machine; passenger volume prediction; mutual information method

Abstract

This article proposes a new method for prediction of public transit passenger volume based on phase space reconstruction and support vector machine (SVM); applies mutual information method in calculating the optimal time delay of time series of public transit passenger volume; applies Cao’s method in calculating the optimal embedding dimension; then calculates out the Lyapunov exponent, evidencing that passenger volume chaos phenomena exists. It establishes phase space reconstruction – support vector machine prediction model as well as determines the pairs of training sample for prediction of the real passenger volume. It is proved through actual examples that this method can predict passenger volume effectively.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xue Xiang-hong Xuex
AU  - Xiao-feng Xue
AU  - Xu Lei Xu X.
PY  - 2015/04
DA  - 2015/04
TI  - A New Phase Space Reconstruction Method for Prediction of Public Transit Passenger Volume
BT  - Proceedings of the 2015 International Conference on Intelligent Systems Research and Mechatronics Engineering
PB  - Atlantis Press
SP  - 1053
EP  - 1057
SN  - 1951-6851
UR  - https://doi.org/10.2991/isrme-15.2015.220
DO  - 10.2991/isrme-15.2015.220
ID  - Xuex2015/04
ER  -