Urban Road Travel Time Prediction based on ELM

DOI

10.2991/icamcs-16.2016.83How to use a DOI?

Keywords

Intelligent transportation systems(ITSs),TTP,ELM,prediction Model.

Abstract

The Travel Time Prediction (TTP) is an important element in the study of the advanced transportation guidance system and control system. In this paper, an advanced method with Extreme Learning Machine algorithm(ELM) has been discussed by analyzing the various travel time prediction method. The feasibility and advantages of Extreme Learning Machine in travel time prediction has been studied, and the comparisons between ELM and SVR and BPNN has been detaily discussed. Moreover, the traffic data, which is collected from REGIOLAB-DELFT platform, have been used for validation. The results show that the ELM algorithm outperforms the related value to those by SVR and BPNN.

Copyright

© 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/).

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TY  - CONF
AU  - Lun Li
AU  - Dong Wang
AU  - Zhu Xiao
AU  - Xiaohong Li
PY  - 2016/06
DA  - 2016/06
TI  - Urban Road Travel Time Prediction based on ELM
BT  - Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
PB  - Atlantis Press
SP  - 392
EP  - 395
SN  - 2352-5401
UR  - https://doi.org/10.2991/icamcs-16.2016.83
DO  - 10.2991/icamcs-16.2016.83
ID  - Li2016/06
ER  -