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Multi-phase time series models for motorway flow forecasting

机译:高速公路流量预测的多相时间序列模型

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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.
机译:在本研究中,提出了一种用于解决高速公路流预测问题的多相时间序列预测方法。这里介绍的方案基于从荷兰阿姆斯特丹的密集使用环路收集的流动模式进行了广泛的研究。这里提出的新预测方法基于多相信息提取,其最终目标是预测网络的边界点处的交通状态。利用其简单的架构,使得提出实际应用的兴趣方法,与现有模型相比,实现了显着的改进。在其一般形式中,所提出的方法可以处理维度的诅咒,与输入空间的尺寸的数量相关联。

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