Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)

Short-term traffic flow forecasting based on SVR

Authors
Yuanyuan Li, Weixiang Xu
Corresponding Author
Yuanyuan Li
Available Online May 2018.
DOI
https://doi.org/10.2991/amcce-18.2018.10How to use a DOI?
Keywords
Short-term Traffic flow forecasting; Phase Space Reconstruction; KNN; SVR.
Abstract
This paper constructs a short-term traffic flow forecasting model based on SVR. First, the modified KNN algorithm is applied to achieve phase space reconstruction and get the input data of SVR. Then, the short-term traffic flow forecasting model is established. Finally, this model was tested and evaluation indexes of traffic flow model were analyzed using the open microwave data provided by the OpenITS system. The results were compared with neural network and conventional SVR model and it shows that the model has better prediction performance.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
Part of series
Advances in Engineering Research
Publication Date
May 2018
ISBN
978-94-6252-508-5
ISSN
2352-5401
DOI
https://doi.org/10.2991/amcce-18.2018.10How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yuanyuan Li
AU  - Weixiang Xu
PY  - 2018/05
DA  - 2018/05
TI  - Short-term traffic flow forecasting based on SVR
BT  - 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.10
DO  - https://doi.org/10.2991/amcce-18.2018.10
ID  - Li2018/05
ER  -