Based on Data Fusion Intelligent Traffic Information Analysis and Optimization

Yuan Zhang Lu; Bing Zhang

doi:10.4028/www.scientific.net/AMM.568-570.831

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 568-570Based on Data Fusion Intelligent Traffic...

Based on Data Fusion Intelligent Traffic Information Analysis and Optimization

Abstract:

In this paper, we propose an analysis refine scheme based on data fusion towards some existing problems in data analysis of intelligent transportation systems .This method constructed the data into a plurality of time-series according to the characteristics of each attribute data. Providing an objective scientific basis for dynamic traffic management through intelligent analysis of traffic information based on the gray advantage analysis among data and system model of Intelligent Traffic Information decision support and auxiliary decision analysis.

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Periodical:

Applied Mechanics and Materials (Volumes 568-570)

Pages:

831-834

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.568-570.831

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Online since:

June 2014

Authors:

Yuan Zhang Lu*, Bing Zhang

Keywords:

Data Fusion, Data Optimization, Gray Advantage Analysis, Intelligent Transportation System (ITS)

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* - Corresponding Author

References

[1] Shraga Shoval, JeffP Zyburt. Robot diver for guidance of automatic durability road test vehicle. Proceedings of IEEE International Conference on Robotics & Automation . 131-134，(2009).

DOI: 10.1109/robot.1998.677422

Google Scholar

[2] M. Koker. Review of Multisensor Data Fusion Architectures and Techniques. IEEE Int. System On Intelligent Control . 86-88，(1993).

Google Scholar

[3] Surphan Thawornwong, David Enke. The Adaptive Selection of Financial and Economic Variables for Use with Artificial Neural Networks[J]. Neuorcomputing. 56: 205-232，(2004).

DOI: 10.1016/j.neucom.2003.05.001

Google Scholar

[4] X.W. Dai M.A. Ferman R.P. Roesser. A simulation evaluation of a real-time traffic information system using probe vehicles. Proceedings of the IEEE Intelligent Transportation Systems . (2003).

DOI: 10.1109/itsc.2003.1251999

Google Scholar

[5] Lianghua He, Xiaodong Hou, Laibao Yu. Networked information collected in the Intelligent Transportation System [J]. Control system . 2008 . 4 (3) : 29-32(In Chinese).

Google Scholar

[6] David M eignan, O livier Simonin, A bderrafiaa Kou2kam. Simulation and evaluation of urban busnet works using a multiagent approach. Simulation Modeling Pract ice Theory . (2007).

Google Scholar