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TRAFFIC VOLUME FORECASTING OF URBAN HIGHWAY IN SHANGHAI.
| 题名： | TRAFFIC VOLUME FORECASTING OF URBAN HIGHWAY IN SHANGHAI. |
| 作者： | Chen-Z; Qiao-H; Fei-S |
| 关键词： | Forecasting-; Information-technology; Networks-; Real-time-information; Time-domain-analysis; Traffic-volume; Transportation-engineering; Urban-highways |
| 摘要： | 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. |
| 总页数： | Conference Title: 9th World Congress on Intelligent Transport Systems. Location: Chicago, Illinois. Sponsored by: ITS America, ITS Japan, ERTICO (Intelligent Transport Systems and Services-Europe). Held: 20021014-20021017. 2002. pp7 |
| 报告类型： | 科技报告 |
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