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空中交通管理中的拓数据分析:大飞行数据集的形状

Manuel Cuerno^1,2, Luis Guijarro², Rosa María Arnaldo Valdés³

¹Department of Mathematics, CUNEF University, Madrid, Spain.

|February 27, 2025

概括

拓数据分析 (TDA) 通过从飞行轨迹和延误中创建机场"足迹"来提供对空中交通管理 (ATM) 数据的新见解. 这种方法成功地对西班牙机场进行了分类,证明了TDA在航空数据分析方面的潜力.

科学领域:

数据科学数据科学数据科学
计算拓学的计算拓学
航空分析航空分析

背景情况:

分析复杂的飞行轨迹数据集是具有挑战性的,因为高维度和相互连接.
拓数据分析 (TDA) 是一种通过专注于拓特征来分析高维数据的强大方法.
现有的研究强调了TDA在航空领域的普遍适用性,但对大量的ATM数据缺乏全面的应用.

研究的目的:

引入拓数据分析 (TDA) 和其工具,从空中交通管理 (ATM) 数据中提取有意义的见解.
证明TDA的应用,特别是持久性景观,用于生成机场特定的足迹.
通过将其应用于西班牙机场来验证TDA在分析真实世界ATM数据中的有效性.

主要方法:

在飞行轨迹数据集上使用拓数据分析 (TDA) 技术.
采用了TDA工具的持久性景观,以生成独特的机场足迹.
一个特定时期的平均持久性景观,包括2018年夏季西班牙机场的轨迹偏差和延误.

主要成果:

使用TDA生成了不同的机场足迹,反映了轨道偏差和延误.
来自TDA的机场足迹与西班牙机场的既定分类保持一致.
该分析作为概念验证,突出了TDA在ATM数据分析方面的能力.

结论:

拓数据分析 (TDA) 是一种强大的方法,可以从复杂的ATM数据中获得洞察力.
持久性景观可以有效地基于飞行数据来描述机场行为.
这项研究为TDA在应对ATM挑战方面的未来应用提供了基础.

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