A new method for short-term traffic flow forecasting based on chaotic time series analysis

被引：0
|
作者：
Jiang, HF [1 ]
Wei, XY [1 ]
Zhang, Y [1 ]
机构：
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
来源：
ICEMI 2005: CONFERENCE PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOL 3 | 2005年
关键词：
short-term traffic flow; adding-weight one-rank local-region; chaotic time series forecasting; chaos;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
On the basis of analysis of the time series of urban short-term traffic flow and the characteristic of chaos, this paper proposes a short-term traffic flow forecasting method through study on chaotic time series forecasting models. This method is based on adding-weight one-rank local-region (AWORLR) model. Weights are introduced and they make this method more adaptive and precise than whole-region methods. The forecasting result of actual short-time traffic flow is satisfying.
引用
收藏
页码：65 / 68
页数：4
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