摘要
智能交通运输系统是目前国际公认的解决交通拥堵、提高运行效率的最佳途径,交通流的实时、准确预测是智能交通运输系统的核心技术之一;在对目前几种常见的交通流预测模型的基础上,提出一种基于微粒群算法的组合预测;新方法充分考虑了各种算法的优点,并结合重庆市某道路进行实证分析。
Intelligent Transportation Systems are well known as the best way to improve operational efficiency and to solve traffic jams, real time and accurate forecast of traffic flow is one of the critical technologies of Intelligent Transportation Systems. In this paper, on the basis of analysis of common traffic flow predictive model, combined prediction of traffic flow based on Particle Swarm Optimization was given. The new method sufficiently considers the advantages of many algorithms, in the end, an empirical analysis was conducted based on a road of Chongqing.
出处
《重庆工商大学学报（自然科学版）》
2011年第1期52-54,共3页
Journal of Chongqing Technology and Business University:Natural Science Edition
关键词
智能交通
微粒群算法
组合预测
intelligent transportation
Particle Swarm Optimization
combined prediction
作者简介
卞鹏（1985-），男，山东莱芜人，硕士研究生，从事经济统计分析与决策研究．
