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- W2910197777 abstract "With the implementation of the freeway free policy during the holidays, traffic congestion in the freeway becomes a common phenomenon. In order to alleviate traffic pressure, traffic flow prediction during the holidays has become a problem of great concern. This paper proposes a hybrid prediction methodology combining discrete Fourier transform (DFT) with support vector regression (SVR). The common trend in the traffic flow data is extracted using DFT by setting an appropriate threshold, which is predicted by extreme extrapolation of the historical trend. The SVR method is applied to predict the residual series. The experimental results with measured data collected from the toll stations in Jiangsu province of China show that the proposed algorithm has higher accuracy compared with the traditional method, and it is an efficient method for traffic flow prediction during the holidays." @default.
- W2910197777 created "2019-01-25" @default.
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- W2910197777 date "2019-01-20" @default.
- W2910197777 modified "2023-10-18" @default.
- W2910197777 title "Traffic Flow Prediction during the Holidays Based on DFT and SVR" @default.
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- W2910197777 doi "https://doi.org/10.1155/2019/6461450" @default.
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