物理学报Issue(14)：1-8,8.DOI:10.7498/aps.63.140504
基于能力区域的交通状态预测方法
Traffic state prediction based on comp etence region
摘要
Abstract
Traffic state prediction is a key basis of traffic flow guidance system and traffic information publishing system. This paper presents a new method of forecasting the traffic state of unban expressway based on competence region. This method can predict the traffic state grade of road based on the distance between the sample data and the traffic state cluster center by creating a competence region of neural network classifier. And this method can effectively integrate the temporal and spatial features together without considering the correlation between the different features, and thus it has a strong adaptability. The experimental results show that this traffic state prediction method can reduce the prediction error and improve the equality coefficients compared with the classical algorithms. The prediction method used in this paper is effective and accurate for forecasting traffic state based on the competence region.关键词
交通状态/预测/交通参数/聚类Key words
traffic state/prediction/traffic parameter/cluster引用本文复制引用
刘擎超,陆建,陈淑燕..基于能力区域的交通状态预测方法[J].物理学报,2014,(14):1-8,8.基金项目
国家高技术研究发展计划(批准号:2011AA110302)和江苏省普通高校研究生科研创新计划(批准号：CXZZ13_0119)资助的课题 （批准号:2011AA110302）
