Short-term traffic flow forecasting based on SVR

DOI

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.

Copyright

© 2018, 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  - Yuanyuan Li
AU  - Weixiang Xu
PY  - 2018/05
DA  - 2018/05
TI  - Short-term traffic flow forecasting based on SVR
BT  - Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SP  - 57
EP  - 61
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.10
DO  - 10.2991/amcce-18.2018.10
ID  - Li2018/05
ER  -