交通信息与安全2011，Vol.29Issue(4)：58-61,4.DOI:10.3963/j.ISSN1674-4861.2011.04.013
混合智能算法在城市道路短时交通流量预测中的研究
Hybrid Intelligent Model for Urban Road Short Time Traffic Flow Prediction
石永辉 1鲍俊 2严忠贞 3蒋圣萍2
作者信息
- 1. 武汉市公安局交通管理局 武汉430022
- 2. 武汉捷讯信息技术有限公司 武汉430074
- 3. 武汉理工大学智能交通系统研究中心 武汉430063
- 折叠
摘要
Abstract
Accurate and reliable short time traffic flow forecasting of urban road is one of the most important issues in the traffic information management. Due to the nonlinear and stochastic of the data, it is often difficult to predict the traffic flow precisely via a certain method. Hence, a new hybrid intelligent forecasting approach based on the integration of wavelet transform (WT), particle swarm optimization (PSO) and support vector machine (SVM) is proposed for the short time traffic flow prediction in this paper. The advantage of the proposed method is that the combination of wavelet transform and SVM can deal with the nonlinear and stochastic characteristics of the original data well. The forecasting rate may be enhanced by using this new technique. Furthermore, 360 samples of the practical traffic flow data are applied to the validation of the proposed prediction model. The analysis results show that the proposed method can extract the underlying rules of the testing data and improve the prediction accuracy by 9% or better when compared with SVM approach.关键词
交通流量/短时预测/小波变换/粒子群算法/支持向量机Key words
traffic flow/short time prediction/wavelet transform/PSO/SVM分类
通用工业技术引用本文复制引用
石永辉,鲍俊,严忠贞,蒋圣萍..混合智能算法在城市道路短时交通流量预测中的研究[J].交通信息与安全,2011,29(4):58-61,4.
