Indicator of serious flight delays with the approach of time-delay stability
Indicator of serious flight delays with the approach of time-delay stability
复制标题
接近时滞稳定性的严重航班延误指标
DOI：
10.1016/j.physa.2018.11.038
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Hu Chin-Kun
中科院分区：
文献类型：
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作者：
Wang Yan-Jun;Zhu Yun-Feng;Zhu Chen-Ping;Wu Fan;Yang Hui-Jie;Yan Yong-Jie;Hu Chin-Kun
旅客航班延误是世界各地机场普遍存在的现象，它不仅造成空中交通秩序的混乱，航空公司的经济损失，而且降低了数百万人的出行质量。从统计物理学的观点出发，基于真实的数据的研究是很少见的。在本工作中，我们下载并纯化了美国交通统计局20多年来积累的此类延误记录的大数据。我们考虑的出发和到达记录的航班之间的某些对机场的时间序列，并纠正他们通过定义无量纲速度的航班。此外，我们发现这种时间序列之间的时滞稳定性的方法，并描述与相关状态的时间网络的相关性的变化。在最长记录航班的不同抽样组中，验证了时间网络的平均度与航班延误率之间的确定性对应关系。网络的平均关联度通常先于高延误率的峰值出现，这是航班严重延误预警的一个指标。
Passenger flight delays, causing much disorder of air traffics, economic losses of airlines, and downgrading the travel quality of millions of people, are ubiquitous phenomena in airports all over the world. Investigation based on real data from the view point of statistical physics is rarely seen. In the present work, big data of such delay records over 20 years accumulated by Bureau of Transportation Statistics in the United States are downloaded and purified by us. We account the departure and arrival records of such flights between certain pair of airports as time series, and rectify them by defining dimensionless velocity of the flights. Furthermore, we find the varying cross-correlations among such time series with the approach of time delay stability, and describe the correlations with temporal networks for correlation states. Deterministic correspondences between the average degrees of temporal networks and delay ratios of passenger flights are verified in different sampling groups of flights with the longest records. The mean degrees of correlation networks usually emerge a peak prior to that of high delay ratios, which serves an indicator for the precaution to serious flight delays.