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- W623269193 abstract "Forecasting traffic volume is an important task in guiding drivers' routes controlling urban highways, and providing real-time transportation information. In this study, neural network models are used to forecasting traffic volume. First the Rescaled Range (R/S) analysis is used to identifying traffic volume data trends, fluctuations and randomness. Then Time-delayed recurrent network is used to forecast the traffic volume in the next 15 minutes. The experiments show that the traffic volume forecasting based on recurrent model has a good performance." @default.
- W623269193 created "2016-06-24" @default.
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- W623269193 date "2002-01-01" @default.
- W623269193 modified "2023-09-26" @default.
- W623269193 title "TRAFFIC VOLUME FORECASTING OF URBAN HIGHWAY IN SHANGHAI" @default.
- W623269193 hasPublicationYear "2002" @default.
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