期刊文献+

基于协整理论的短时交通流组合预测研究 被引量:7

Short-Term Traffic Flow Combination Forecast by Co-integration Theory
下载PDF
导出
摘要 交通流短时预测是智能交通系统中的一个重点问题,预测效果的好坏直接关系到控制和诱导的结果,是实现先进交通管理信息系统的关键技术之一.本文简要介绍了协整和误差修正模型的概念,利用序列的协整性来进行交通流组合预测模型的有效性验证,并利用误差修正模型提高组合预测模型的稳定性.我们利用北京市二环路上采集到的交通流数据进行了模型的验证.研究结果表明,基于协整理论的交通流组合预测模型可以取得很好的预测效果. Short-term traffic flow prediction is a priority issue of intelligent transportation system.The accuracy of the prediction results directly affects the traffic control and management.Therefore,it is the key technology for the advanced traffic management information system.This paper briefly describes the concept of co-integration and error correction model,and then verifies the validity of the combination of traffic flow forecasting model using the co-integration of series.It also improves the stability of the combination forecasting model through the error correction model.The historical and real-time traffic flow data,collected form the Second Ring Road of Beijing,are used to verify the model.The results indicate that the combination model based on the co-integration and error correction model meets the actual traffic flow characteristics well and obtains a better prediction result.
出处 《交通运输系统工程与信息》 EI CSCD 2011年第3期71-75,共5页 Journal of Transportation Systems Engineering and Information Technology
基金 北京市自然科学基金项目(4102038) 北京市科技计划(D07020601400704)
关键词 智能交通 协整理论 组合预测模型 误差修正 短时交通流预测 intelligent transportation co-integration theory combination forecasting model error correction short-term traffic flow prediction
  • 相关文献

参考文献7

二级参考文献13

共引文献75

同被引文献62

  • 1武旭,胡思继,崔艳萍,马叶江.铁路运输与社会经济协调发展评价问题的研究[J].铁道学报,2005,27(3):20-25. 被引量:19
  • 2姚智胜,邵春福,高永亮.基于支持向量回归机的交通状态短时预测方法研究[J].北京交通大学学报,2006,30(3):19-22. 被引量:51
  • 3Dijkstra E. A note on two problems with graphs[J].{H}NUMERISCHE MATHEMATIK,1959,(01):269-271. 被引量:1
  • 4Zhan F B,Noon C E. Shortest path algorithms:an evaluation using real road networks[J].{H}Transportation Science,1998,(01):65-73. 被引量:1
  • 5Hart P,Nilsson N,Raphael B. A formal basis for the heuristic determination of minimum cost paths[J].IEEE Trans Syst Science and Cybernetics,1968,(02):100-107. 被引量:1
  • 6Brinkho T. A framework for generating network-based moving objects[J].Geolnformatica,2002,(02):153-180. 被引量:1
  • 7Malandraki C,Daskin M S. Time dependent vehicle routing problems:for-mulations,properties and heuristic algorithms[J].{H}Transportation Science,1992,(03):185-200. 被引量:1
  • 8Donati A V,Montemanni R,Casagrande N. Time dependent vehicle routing problem with a multi ant colony system[J].{H}European Journal of Operational Research,2008,(03):1174-1191.doi:10.1016/j.ejor.2006.06.047. 被引量:1
  • 9Donati A V,Montemanni R,Casagrande N. Time dependent vehicle routing problem with a multi ant colony system[J].{H}European Journal of Operational Research,2008,(03):1174-1191.doi:10.1016/j.ejor.2006.06.047. 被引量:1
  • 10Tavakkoli-Moghaddam R,Gazanfari M,Alinaghian M. A new mathematical model for a competitive vehicle routing problem with time windows solved by simulated annealing[J].{H}JOURNAL OF MANUFACTURING SYSTEMS,2011,(02):83-92. 被引量:1

引证文献7

二级引证文献59

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部