重庆交通大学学报(自然科学版) ›› 2008, Vol. 27 ›› Issue (1): 96-99.
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范鲁明, 贺国光
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FAN Lu-ming, HE Guo-guang
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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
中图分类号:
U491.1
范鲁明, 贺国光. 改进非参数回归在交通流量预测中的应用[J]. 重庆交通大学学报(自然科学版), 2008, 27(1): 96-99.
FAN Lu-ming, HE Guo-guang. Application Improvement of Nonparametric Regression to Traffic Flow Forecast[J]. Journal of Chongqing Jiaotong University(Natural Science), 2008, 27(1): 96-99.
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http://xbzk.cqjtu.edu.cn/CN/Y2008/V27/I1/96