Research on the Real-Time Prediction Model of the Traffic Flow Based on Wavelet Neural Network

Abstract:

Real-time traffic flow prediction is the core of traffic control and management, which is the basis of traffic safety in mountain area. 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. Considering these features, this paper deals specially with this issue based on Wavelet neural network. Besides, by taking a road in mountain area for example, the paper realizes the analog simulation through the Matlab software programming. And the simulation results show that the traffic flow can be precisely forecast using Wavelet neural network, and its value is close to the expectations. The MAE of the Wavelet neural network is 20.1074 and the MSE is 2.5254.

• Periodical: Applied Mechanics and Materials (Volumes 241-244)
• Pages: 2088-2094
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.241-244.2088
• Online since: December 2012
• Authors: Hui Ying Wen, Gui Feng Yang, Wei Tiao Wu
• Keywords: Time Sequence Forecast, Traffic Flow Forecasting, Traffic Flow in Mountain Area, Wavelet Neural Network (WNN)

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