Short-Term Prediction of Intelligent Traffic Flow Based on BP Neural Network and ARIMA Model

Feiqi Deng,Xin Guo

doi:10.1109/iceee.2010.5660398

Short-Term Prediction of Intelligent Traffic Flow Based on BP Neural Network and ARIMA Model

Feiqi Deng, Xin Guo

https://doi.org/10.1109/iceee.2010.5660398

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Publication Date: Nov 1, 2010

Citations: 10

Affiliation: South China University of Technology

#Back Propagation Neural Network #Short-term Prediction Of Traffic Flow + Show 8 more

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Abstract

Short-term prediction of intelligent traffic flow is in favor of road unblocked and vehicle waiting strategy. The algorithm of short-term prediction of intelligent traffic flow based on back propagation(BP) neural network and autoregressive integrated moving average （ARIMA） model can solve it partially. Firstly, Establishing a BP neural network sub-model and ARIMA sub-model, Then taking BP neural network as the approaching machine of the most superior nonlinear combination model to establish the hybrid prediction model, and the results indicate that the hybrid prediction method is practical and feasible.

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