Olivares Felipe, Marín-Rodríguez F Javier, Acharya Kishor, Zanin Massimiliano
Instituto de Física Interdisciplinar y Sistemas Complejos (CSIC-UIB), Campus UIB, 07122 Palma, Spain.
Entropy (Basel). 2025 Feb 23;27(3):230. doi: 10.3390/e27030230.
Functional networks have become a standard tool for the analysis of complex systems, allowing the unveiling of their internal connectivity structure while only requiring the observation of the system's constituent dynamics. To obtain reliable results, one (often overlooked) prerequisite involves the stationarity of an analyzed time series, without which spurious functional connections may emerge. Here, we show how ordinal patterns and metrics derived from them can be used to assess the effectiveness of detrending methods. We apply this approach to data representing the evolution of delays in major European and US airports, and to synthetic versions of the same, obtaining operational conclusions about how these propagate in the two systems.
功能网络已成为分析复杂系统的标准工具，它能够揭示系统的内部连接结构，同时只需要观察系统的组成动态。为了获得可靠的结果，一个（常常被忽视的）前提条件是所分析时间序列的平稳性，否则可能会出现虚假的功能连接。在这里，我们展示了如何使用从序数模式及其衍生的指标来评估去趋势方法的有效性。我们将这种方法应用于代表欧洲和美国主要机场延误情况演变的数据，以及相同数据的合成版本，从而得出关于这些延误在两个系统中如何传播的实际结论。
