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Real-time Traffic Flow Forecasting based on Wavelet Neural Network
Journal Title International Journal of Online Engineering (iJOE)
Journal Abbreviation i-joe
Publisher Group International Association of Online Engineering (IAOE)
Website http://online-journals.org
   
Title Real-time Traffic Flow Forecasting based on Wavelet Neural Network
Authors Li, Rihan; Xu, Jianmin; Luo, Qiang; Hu, Sangen
Abstract Real-time traffic flow forecasting is the core of Intelligent Transportation System (ITS), and the foundation of multi-subsystem’s implementation in ITS. Traffic flow, which is highly time-relevant, with the features of high non-linear and non-determinism, can be treated as the time sequence forecast. On the basis of these features of traffic flow, this paper tries to deal with this issue based on Wavelet Neural Network (WNN) specially. At the same time, the paper realizes the analogue simulation through the Matlab software programming, by taking a road for example. And the simulation results show that the traffic flow can be precisely forecasted using Wavelet Neural Network, and its value is close to the expectations.
Publisher kassel university press GmbH
Date 2013-06-11
Source 1868-1646
Rights The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
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