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     Research Journal of Applied Sciences, Engineering and Technology


Data-Fusion Approach Based on Evidence Theory Combining with Fuzzy Rough Sets for Urban Traffic Flow

Ning Chen
School of Mechanical and Automotive Engineering, Zhejiang University of Science and Technology, Hangzhou 310023, China
Research Journal of Applied Sciences, Engineering and Technology  2013  11:1993-1997
http://dx.doi.org/10.19026/rjaset.6.3814  |  © The Author(s) 2013
Received: November 24, 2012  |  Accepted: January 17, 2013  |  Published: July 25, 2013

Abstract

The traffic detecting result is always short of accuracy by different kinds of individual sensors in urban China. A new data fusion approach is raised in this paper to solve the issue, based on fuzzy rough set theory combining with evidence theory. The method is improved to concise attribute rules and to measure fuzzy likelihood. Furthermore, a new combination rule is given to dissolve the confliction among the traffic evidence data collected by different individual sensors. Finally, the experiment to fuse the traffic data from an intersection in Hangzhou City showed that the proposed approach could obtain a high accuracy.

Keywords:

Combination rule, data confliction, data fusion, intelligent transportation system, urban traffic flow,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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