摘要
为应用非线性理论对空中交通流量进行实时分析和短期预测提供合理性判据,研究了空中交通流量时间序列的平稳性和非线性检验方法。首先,选取三亚4号扇区40 d的数据,以15 min为统计间隔,构建交通流量时间序列;接着采用基于自相关图的定性方法以及基于ADF(augmented Dickey-Fuller test)和PP(Phillips-Perron)检验的定量方法分析所构建时间序列的平稳性;然后利用替代数据法研究时间序列的非线性;最后分析时序长度、时间延迟和统计尺度等对非线性的影响。结果显示:时间序列的自相关系数呈快速下降、趋近于0的趋势,且时序数据生成过程不存在单位根,说明时间序列平稳;以三阶时间逆不对称性、三阶自相关和三阶自协方差为检验统计量,拒绝零假设3,说明时间序列具有非线性成分,且该成分源自系统自身动力学过程;长时序往往体现出较为稳定的非线性,短时序往往体现不出非线性;时间延迟对三阶时间逆不对称性统计量影响较大,对其他统计量影响较小;30 min尺度的流量时序更适用于三亚4号扇区流量的短期预测。
In order to provide a reasonable criterion for the real-time analysis and short-term prediction of air traffic flow based on nonlinear theory,the stationarity and nonlinearity test methods of air traffic flow time series are studied.Firstly,the time series of traffic flow is constructed with 40-day data and 15-minute statistical interval from sector 4 of Sanya,Haina Province.Secondly,the stability of the time series is analyzed by both qualitative method based on autocorrelation graph and quantitative method based on ADF (augmented Dickey-Fuller test) and PP(Phillips-Perron) test;Then,the nonlinearity of the time series is studied by using surrogate data method;Finally,the effects of length,time delay and statistical scale on nonlinearity are analyzed.Results show that the autocorrelation coefficient of time series decreases rapidly and tends to zero,and there is no unit root in the generation process of time series data,which indicates that time series is stationary.The third-order time inverse asymmetry,third-order autocorrelation and third-order autocovariance are used as test statistics,and the third null hypothesis is rejected,which indicates that time series has a non-linear component,and the component originates from the dynamic process of the system itself.In addition,long-length time series often reflects more stable nonlinearity,and short-length time series often does not reflect non-linearity.Time delay has a greater impact on the third-order statistics of time inverse asymmetry,but a smaller impact on the statistics.Time series with 30-minute scale is more suitable for short-term prediction of Sanya No.4 Sector.
作者
王飞
WANG Fei(College of Air traffic Management,CA UC,Tianjin 300300,China)
出处
《中国民航大学学报》
CAS
2021年第2期1-6,11,共7页
Journal of Civil Aviation University of China
基金
国家自然科学基金项目(71801215,U1833103)
中央高校基本科研业务费专项(3122019129)。
关键词
航空运输
空中交通流
平稳性
非线性
时间序列
air transportation
air traffic flow
stationarity
nonlinearity
time series
