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城市交通流量的非线性混沌预测模型研究
引用本文:黄鹍,陈森发,周振国,亓霞.城市交通流量的非线性混沌预测模型研究[J].东南大学学报,2003,19(4):410-413.
作者姓名:黄鹍  陈森发  周振国  亓霞
作者单位:东南大学经济管理学院,南京210096
摘    要:为了解决日益严重的城市交通问题,本根据交通流已被证明的混沌特性,尝试采用非线性混沌模型来分析交通流时间序列.该模型首先将交通流时间序列在相空间中重构,以充分提取交通流中的相关信息,在此基础上,应用混沌理论对重构信息构材预测方程,并运用遗传算法对模型参数进行了优化辨识,以获得最佳的预测效果.实际的城市交通流量预测研究表明,该模型具有较高的预测精度,可以为城市交通规划和控制提供准确的参考.

关 键 词:混沌理论  交通流  遗传算法  流量预测  交通规划

Research on a non-linear chaotic prediction model for urban traffic flow
Huang Kun,Chen Senfa,Zhou Zhenguo,Qi Xia.Research on a non-linear chaotic prediction model for urban traffic flow[J].Journal of Southeast University(English Edition),2003,19(4):410-413.
Authors:Huang Kun  Chen Senfa  Zhou Zhenguo  Qi Xia
Abstract:In order to solve serious urban transport problems, according to the proved chaotic characteristic of traffic flow, a non linear chaotic model to analyze the time series of traffic flow is proposed. This model reconstructs the time series of traffic flow in the phase space firstly, and the correlative information in the traffic flow is extracted richly, on the basis of it, a predicted equation for the reconstructed information is established by using chaotic theory, and for the purpose of obtaining the optimal predicted results, recognition and optimization to the model parameters are done by using genetic algorithm. Practical prediction research of urban traffic flow shows that this model has famous predicted precision, and it can provide exact reference for urban traffic programming and control.
Keywords:traffic flow  chaotic theory  phase reconstruction  non  linear  genetic algorithm  prediction model
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