量化高斯度的偏差与飞行延迟分布的应用
Felipe Olivares1, Massimiliano Zanin1
1Instituto de Física Interdisciplinar y Sistemas Complejos (CSIC-UIB), Campus UIB, 07122 Palma, Spain.
Entropy (Basel, Switzerland)
|April 26, 2025
概括
我们介绍了一种新方法,使用詹森-香农距离来测量数据中高斯度的偏差. 对航班延误的分析揭示了显著的非高斯模式,特别是在繁忙的机场,这表明不同的空中交通管理策略.
科学领域:
- 统计 统计 统计 统计
- 数据分析 数据分析
- 空中交通管理是指空中交通管理.
背景情况:
- 高斯分布是数据分析中常见的假设.
- 从高斯度的偏差,以斜率和重尾为特征,可以影响模型的准确性.
- 了解这些偏差对于像空中交通这样的复杂系统至关重要.
研究的目的:
- 开发一种新的方法来量化高斯度的偏差.
- 用稳定的分布分析斜度和重尾的影响.
- 通过真实世界的航班延误数据来验证方法.
主要方法:
- 使用Jensen-Shannon距离来测量统计差异.
- 采用稳定分布作为灵活的建模框架.
- 用阶段随机化替代品作为高斯引用进行比较.
- 用欧洲和美国航班延误数据集验证了该方法.
主要成果:
- 在航班延误数据中显示出高斯度的显著偏差.
- 在高流量机场发现了特别明显的偏差.
- 在欧洲和美国之间观察到空中交通模式的系统差异.
结论:
- 提出的詹森-香农距离方法有效量化非高斯性.
- 航班延误与高斯假设有很大的偏差,特别是在繁忙的空域.
- 这些发现表明,欧洲和美国的空中交通管理策略存在根本差异.
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