【摘要】 为了提高道路断面短时交通流预测的精确性,本文对道路断面的短时交通流数据进行混沌时间序列分析,并对多维交通流时间序列数据进行了相空间重构,建立基于混沌时间序列分析的道路断面短时交通流预测模型,利用粒子群优化算法优化模型的参数选择。最后应用本文的方法对城市快速路采集的断面交通流数据进行分析,对道路断面短时交通流建立预测模型并验证其有效性。更多还原

【Abstract】 In order to improve the prediction pricesion of the short-term traffic flow of road cross section, by chaotic time series analysis and the phase space reconstruction of the multi-dimensional short-term traffic flow data, a short-term traffic flow forecast model of road cross section based on chaotic time series analysis was put forward. The parameters of the forecast model was optimized with the particle swarm optimization algorithm. Meanwhile, the forecast model proposed in the paper were tested by the real-time traffic flow data from a urban expressway,the results were satisfying.更多还原