Traffic Data Fusion Research Based on Numerical Optimization BP Neural Network

Yuan Li Gu; Xing Chuan Wang; Jian Xiang Xu

doi:10.4028/www.scientific.net/AMM.513-517.1081

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Traffic Data Fusion Research Based on Numerical...

Traffic Data Fusion Research Based on Numerical Optimization BP Neural Network

Abstract:

The collection and management of dynamic traffic information is one of the most important part of ITS. Its a main task for it to improve the accuracy of the acquisition of the traffic information when facing up with different kinds of traffic detectors. Data fusion method can deal with data from different detectors and improve the accuracy. This paper first analyzed the characters of different traffic detectors, and proposed a method to repair the missing values which is a common phenomenon in the detect data. Then some improvements are made to adjust the BP neural network so that it could be suitable for data fusion. At last, the data fusion of traffic speed from the south of Jianguomen Qiao to the north of Chaoyangmen Qiao on the second ring road of Beijing is given as an example with the comparison of different improve methods of BP neural networks, and it shows that the method given in this passage is efficient in improving the accuracy of the traffic data detection.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

1081-1087

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.1081

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Online since:

February 2014

Authors:

Yuan Li Gu*, Xing Chuan Wang, Jian Xiang Xu

Keywords:

BP Neural Network (BPNN), Data Fusion, Missing Values, Numerical Optimization

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* - Corresponding Author

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