中文核心期刊
CSCD来源期刊
中国科技核心期刊
RCCSE中国核心学术期刊

重庆交通大学学报(自然科学版) ›› 2008, Vol. 27 ›› Issue (1): 96-99.

• • 上一篇    下一篇

改进非参数回归在交通流量预测中的应用

范鲁明, 贺国光   

  1. 天津大学 管理学院 系统工程研究所, 天津 300072
  • 收稿日期:2007-01-28 修回日期:2007-04-03 出版日期:2008-02-20 发布日期:2016-11-14
  • 作者简介:范鲁明(1982-),男,山东济南人,硕士研究生,主要研究领域为智能交通系统,交通系统工程。
  • 基金资助:
    国家自然科学基金资助项目(50478088)

Application Improvement of Nonparametric Regression to Traffic Flow Forecast

FAN Lu-ming, HE Guo-guang   

  1. Institute of Systems Engineering, Tianjin University, Tianjin 300072, China
  • Received:2007-01-28 Revised:2007-04-03 Online:2008-02-20 Published:2016-11-14

摘要: 实时、准确的短时交通流量预测是实现交通控制与诱导的关键。结合模式识别的思想,提出基于模式识别的非参数回归算法,并将之应用于短时交通流量预测,最后用仿真试验检验了方法的有效性,仿真试验结果表明,该方法具有较高的预测精度。

关键词: 短时交通流量预测, 非参数回归, 模式识别

Abstract: Real-time and accurate short-term traffic flow forecast is critical to the traffic control and guidance. The nonparametric regression based on pattern recognition was presented and used for short-term traffic flow forecast. Simulation experiments were conducted to examine the validity of the method. The compute results show that this method has high precision.

Key words: short-term traffic flow forecast, nonparametric regression, pattern recognition

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