A statistical study of the weather impact on punctuality at Frankfurt Airport
A statistical study of the weather impact on punctuality at Frankfurt Airport
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DOI：
10.1002/met.74
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发表时间：
2008-06
影响因子：
2.7
通讯作者：
D. Markovic;T. Hauf;P. Röhner;U. Spehr
中科院分区：
文献类型：
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作者：
D. Markovic;T. Hauf;P. Röhner;U. Spehr
一个混合回归/时间序列模型被用来与总的每日准点率（TOTP）在法兰克福机场，德国，天气，交通流量和机场系统状态。选定的建模方法适用于2001-2006年的年度、多年度和季节数据。通过主成分分析（PCA）方法的应用，实现了初始变量系统维数的降低。在使用自回归（AR）模型校正残差中的自相关性后，可以由模型解释的变异性部分在60%至69%之间。检测到具有统计学意义的模型参数数量存在轻微的年间变异性。在识别特定的终端延迟影响因素后，讨论了1年间隔的24小时准点预测的可能性。版权所有© 2008皇家气象学会
A hybrid regression/time series modelling was used to relate the total daily punctuality (TOTP) at Frankfurt Airport, Germany, to weather, the traffic flow and the airport system state. The selected modelling approach is applied to the annual, the multi‐annual and seasonal data of the years 2001–2006. Reduction of the initial variables system dimension is achieved through the application of the principal component analysis (PCA) method. The portion of the variability that can be explained by the model after correction of autocorrelations in the residuals using autoregressive (AR) models, is between 60 and 69%. A slight year‐to‐year variability in the number of statistically significant model parameters is detected. Upon identification of the terminal‐specific delay impact factors, the possibility of the 24 h punctuality forecast for the interval of 1 year was discussed. Copyright © 2008 Royal Meteorological Society