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针对空中交通流仿真、预测与控制工作中普遍需要空中交通流时空动态基本特征的问题,从混沌与分形角度对交汇航路交通流量时间序列的非线性特征进行了研究.首先,提出了一种基于航路网络结构的交通流识别方法,构建了不同时间尺度下交通流量时间序列;其次,在相空间重构的基础上,利用最大Lyapunov指数定量判断了交通流中混沌特征的存在,并利用递归图分析了不同时间尺度下交通流量时间序列的混沌特征;最后,通过计算关联维数,研究了不同时间尺度下流量时间序列的分形特征.研究结果表明:不同时间尺度下交通流量时间序列均具有混沌特征;当时间尺度为5 min时,流量时间序列的混沌特征最为显著;随着时间尺度增大,流量时间序列的随机性增强,且对系统复杂性的表现能力变弱.
Aiming at the problem that the basic characteristics of the spatial-temporal dynamics of the air traffic flow are generally needed in the simulation, prediction and control of the air traffic flow, the nonlinear characteristics of the time series of the traffic on the converging route are studied from the perspective of chaos and fractal.Firstly, Traffic flow network structure of traffic identification method, traffic time series at different time scales are constructed.Secondly, based on the reconstructed phase space, the maximum Lyapunov exponent is used to quantitatively determine the existence of chaotic features in traffic flow and the recursive graph The chaotic characteristics of traffic flow time series under different time scales are analyzed. Finally, by calculating the correlation dimension, the fractal characteristics of traffic time series at different time scales are studied. The results show that the traffic flow time series have chaos at different time scales Feature. When the time scale is 5 min, the chaotic characteristics of the traffic time series are most notable. As the time scale increases, the randomness of the traffic time series increases and the performance of the system complexity becomes weaker.