Research on traffic flow prediction based on chaos neural network theory

被引：0
|
作者：
Chen, Yong-Hong [1 ]
Juan, Deng [2 ]
机构：
[1] Chongqing Normal Univ, Dept Comp & Math, Chongqing 400047, Peoples R China
[2] Chongqing Univ, Coll Econ & Business Adm, Chongqing 400044, Peoples R China
来源：
WAVELET ACTIVE MEDIA TECHNOLOGY AND INFORMATION PROCESSING, VOL 1 AND 2 | 2006年
关键词：
traffic flow; chaotic prediction; phase reconstruction; neural network theory;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Traffic flow prediction is one of important problem in ITS. Now there are many kinds of algorithm which are based on accuracy and real-time of prediction. In this paper, based on local and add-weight local prediction method of chaos time series, a new kind of prediction algorithm is presented by mix together with their advantage. A unified prediction model can be used for traffic flow forecasting, practical for both condition of local and add-weight local prediction method, but the complexity is not high. Results in experiments shows that it is high accuracy and can be used in traffic flow forecasting.
引用
收藏
页码：628 / +
页数：2
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