Name
Abstract | ||
|---|---|---|
In this study, a multi-phase time series prediction approaches is proposed for solving the motorway flow forecasting problem. The schemes presented here is based on an extensive study of flow patterns that were collected from a densely used ring road of Amsterdam, The Netherlands. The new prediction approach proposed here is based on a multiphase information extraction whose ultimate goal is to forecast traffic states at the boundary points of a network. With its simple architecture that makes the proposed approach of interest of practical application, a significant improvement is achieved in comparison with existing models. In its general form, the proposed approach could handle the curse of dimensionality, a common problem associated with the number of dimensions of input space. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ITSC.2011.6082839 | ITSC |
Keywords | Field | DocType |
automated highways,forecasting theory,knowledge acquisition,road traffic control,roads,time series,curse of dimensionality,flow pattern study,motorway flow forecasting,multiphase information extraction,multiphase time series model,multiphase time series prediction approach,prediction approach,traffic state forecasting,adaptive prediction,demand forecasting,kalman filter,multi-phase time series prediction,support vector machine,traffic flow,forecasting | Data mining,Time series,Traffic flow,Road traffic control,Demand forecasting,Simulation,Support vector machine,Kalman filter,Curse of dimensionality,Information extraction,Engineering | Conference |
ISSN | ISBN | Citations |
2153-0009 | 978-1-4577-2198-4 | 2 |
PageRank | References | Authors |
0.41 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Davarynejad, M. | 1 | 2 | 0.41 |
| Yubin Wang | 2 | 2 | 0.75 |
| Jos Vrancken | 3 | 90 | 13.98 |
| Jan Van Den Berg | 4 | 350 | 35.73 |