Multi-Scale Analyses and Combining Forecasts for Traffic Volumes

被引:0
|
作者
Cao, Minglan [1 ]
Li, Shengli [1 ]
Gao, Danying [2 ]
机构
[1] Zhengzhou Univ, Sch Civil Engn, Zhengzhou 450001, Henan, Peoples R China
[2] Zhengzhou Univ, Zhengzhou 450001, Henan, Peoples R China
基金
中国国家自然科学基金;
关键词
Multiple Scale; Combination Prediction; Exponential Smoothing; Traffic Flow; COMBINATION; WEIGHTS;
D O I
10.4028/www.scientific.net/AMM.488-489.1405
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In view of that the current models are almost combining models of different kinds of forecast methods and the absence of substantial research on multi-scale combining in the context of traffic forecasts, we proposed a method that in multiple scales combines multiple forecasts based on prediction approaches of the same category. The method combines multi-scale analyses with exponential smoothing forecasting and its weights are assigned according to the performance of the various scales' forecasts. Using four years' actual data, we in two scales demonstrated it by forecasting annual traffic volumes for an expressway in China and the application verified its accuracy.
引用
收藏
页码:1405 / +
页数:2
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