| 快速路交通流时间序列聚类预测方法与模型 |
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| 引用本文： | 陈鹏,孙剑,李克平.快速路交通流时间序列聚类预测方法与模型[J].交通与计算机,2008,26(5). |
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| 作者姓名： | 陈鹏 孙剑 李克平 |
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| 作者单位： | 同济大学,上海,201804 |
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| 摘 要： | 针对快速路路段日交通流曲线的相似特性,提出根据天气好、坏,工作日、非工作日作为特性向量,设计一种时间序列聚类算法对不同时间尺度下快速路交通流进行预测.结果显示:此聚类算法与预测模型充分利用了历史数据,30 min时间尺度下预测精度较高,平均绝对相对误差最低为3.34%.
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| 关 键 词： | 交通流特性 时间序列 时间尺度 聚类 预测 |
A Method and Its Model of Expressway Traffic-flow Time Series Clustering Forecast |
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| CHEN Peng,SUN Jian,LI Keping.A Method and Its Model of Expressway Traffic-flow Time Series Clustering Forecast[J].Computer and Communications,2008,26(5). |
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| Authors: | CHEN Peng SUN Jian LI Keping |
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| Institution: | Tongji University;Shanghai 201804;China |
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| Abstract: | Based on the observation of daily similarity of expressway traffic flow data,a new time series clustering algorithm to forecast traffic parameters under different time scales was designed by taking weather and weekday or weekend as classification vectors.The experiment result shows that the time series clustering algorithm and its forecast model make good use of historic data.Its accuracy is quite high under 30-minute time scale with a mean-Absolute-relative-error of 3.34 percent. |
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| Keywords: | traffic flow characteristics time series time scale clustering forecast |
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