%0 Journal Article
%T 交汇航路空中交通流的非线性特征研究<br>Research on Nonlinear Characteristics of Air Traffic Flows on Converging Air Routes
%A 王超
%A 郑旭芳
%A 王蕾&lt
%A br&gt
%A WANG Chao
%A ZHENG Xufang
%A WANG Lei
%J 西南交通大学学报
%D 2017
%R 10.3969/j.issn.0258-2724.2017.01.024
%X 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.<br>： Insights into the temporal and spatial characteristics of air traffic flow is the prerequisite of air traffic flow simulation, prediction and control. Nonlinear characteristics of traffic flow time series on converging air routes were explored from the chaotic and fractal views. First, a traffic flow identification method based on air route network structure was proposed, and air traffic flow time series were constructed on different time scales. Then, based on the reconstruction of phase space, chaos existing in air traffic flow was quantitatively analyzed by the max Lyapunov exponent, and the chaotic characteristics of traffic flow time series on different time scales were analyzed by recurrent maps. Finally, the fractal characteristics of traffic flow time series on different time scales were analyzed using the correlation dimension. The results show that chaos does exist in traffic flow time series on different time scales. The chaotic characteristic of traffic flow time series is the most obvious at the time scale of 5 min. With time scales increasing, the randomness of air traffic flow time series increases, and the ability to show the system complexity becomes weak
%K 空中交通流
%K 非线性时间序列
%K 数据挖掘
%K 混沌
%K 分形
%K &lt
%K br&gt
%K air traffic flow
%K nonlinear time series
%K data mining
%K chaos
%K fractals
%U http://manu19.magtech.com.cn/Jweb_xnjd/CN/abstract/abstract12390.shtml