An ELM-based traffic flow prediction method adapted to different data types
- https://doi.org/10.2991/icimm-16.2016.74How to use a DOI?
- ELM; non-uniform data; traffic flow prediction
Traffic flow prediction has been the crucial aspect in the Intelligent Transport Systems (ITS) and it will help ITS to induce the traffic flow rationally. In this paper, a prediction model based on ELM has been discussed through testing this model with actual data. This model takes advantage of the speed and ability of handling nonlinear system of the ELM algorithm. By analyzing the actual data in Haining County in 2016, the feasibility and advantages of ELM prediction model have been shown when compared with other algorithms. Analyzing the non-uniform and lost data, this model shows the performance that the model can be used in actual application. These characters can remedy the shortcomings which other models have.
- © 2016, 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/).
Cite this article
TY - CONF AU - Xingchao Wang AU - Jianming Hu AU - Yi Zhang AU - Zhenyu Wang PY - 2016/11 DA - 2016/11 TI - An ELM-based traffic flow prediction method adapted to different data types BT - Proceedings of the 6th International Conference on Information Engineering for Mechanics and Materials PB - Atlantis Press SP - 407 EP - 412 SN - 2352-5401 UR - https://doi.org/10.2991/icimm-16.2016.74 DO - https://doi.org/10.2991/icimm-16.2016.74 ID - Wang2016/11 ER -