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

页码：628 / +

页数：2

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