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Space-time correlation analysis of quality-of-service at major US airports-O'Hare International and Minneapolis Airports: a case study

机译：美国主要机场-奥黑尔国际机场和明尼阿波利斯机场的服务质量时空相关性分析：一个案例研究

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In this paper we study and analyze the space-time correlation among different variables in the NAS such as weather, capacity, delay, and cancellation at hub airports. A Quality-of-Service (QoS) Index is formalized as a vector of delay, cancellation and variability of the trade-off relationship between these metrics. A user-friendly graphic tool was first developed in C++/OpenGL to visualize geometrically and chronologically the large, complex data sets of ASPM and BTS. This tool can show how the QoS indexes evolve at major airports visually as time and weather change and help determine their relationships. We next explored the BTS dataset to study the space-time correlations of QoS Indexes for one particular case study involving ORD and MSP airports whose operational correlation can be easily identified by the tool. The analysis was done at the airline level, and revealed patterns of behavior that are airline-specific. Delay and cancellation time series were aggregated using a weighting function for cancellation. Further investigation on Northwest Airlines' aggregated time series showed a significant positive cross-correlation between the airline's late arrivals at ORD and those from ORD to MSP after a time lag of 135 minutes.
机译：在本文中，我们研究和分析了NAS中不同变量之间的时空相关性，例如天气，容量，延误和枢纽机场的取消。服务质量（QoS）索引被正式定义为这些指标之间的权衡关系的延迟，取消和可变性的向量。最初在C ++ / OpenGL中开发了一种用户友好的图形工具，以几何方式和时间顺序可视化ASPM和BTS的大型，复杂数据集。该工具可以直观显示随着时间和天气的变化，主要机场的QoS指数如何变化，并帮助确定它们之间的关系。接下来，我们探索了BTS数据集，以研究涉及ORD和MSP机场的特定案例研究的QoS指数的时空相关性，该工具可以轻松识别其运营相关性。分析是在航空公司级别进行的，并揭示了特定于航空公司的行为模式。延迟和取消时间序列使用加权函数进行汇总以进行取消。对西北航空总时间序列的进一步调查显示，经过135分钟的时间延迟后，该航空公司晚到达ORD的航班与从ORD到达MSP的航班之间存在显着的正相关。

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