Prediction of traffic flow based on the EMD and wavelet neural network

DOI

10.2991/icecee-15.2015.178How to use a DOI?

Keywords

traffic flow; prediction; EMD; wavelet neural network

Abstract

The operation of the urban traffic exist a high degree of complexity and randomness. The key of Intelligent Transportation System is the real-time and accurate traffic flow prediction. Taking effective measures in a timely manner would prevent the occurrence of traffic accidents since traffic congestion brings much traffic inconvenience to people. Real-time traffic flow prediction plays a significant role in easing traffic congestion and guiding convenient travelling. Therefore, considering the characteristics of traffic flow, this paper presents a neural network, wavelet analysis method, and the EMD and wavelet neural network method respectively. Three methods are utilized in simulating the same set of traffic data and then the most effective way of solving traffic congestion is obtained by taking contrast analysis of simulation result.

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  - Teng Feng
AU  - Xiaohong Wang
AU  - Yunlai He
PY  - 2015/06
DA  - 2015/06
TI  - Prediction of traffic flow based on the EMD and wavelet neural network
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 933
EP  - 938
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.178
DO  - 10.2991/icecee-15.2015.178
ID  - Feng2015/06
ER  -