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Multifractal detrended fluctuation analysis on air traffic flow time series: A single airport case

Author

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  • Zhang, Xie
  • Liu, Hongzhi
  • Zhao, Yifei
  • Zhang, Xingchen

Abstract

Exploring multifractal characteristics of air traffic flow time series is helpful in understanding the self-similarity and the correlations embedded in the time series, and thus in obtaining insights into the evolution mechanism and the regular patterns of the air traffic flows, which may help to develop effective air traffic flow management measures. With the multifractal detrended fluctuation analysis method, we identify that the total, the arrival and the departure air traffic flow time series of Beijing Capital International Airport in the summer season of 2017 are of multifractality on the scales below the corresponding crossovers, and the primary cause of the multifractality is the long-range correlations of small and large fluctuations. Comparisons on the multifractality of the time series indicate that the total and the arrival air traffic flows are of the strongest and the weakest multifractality respectively, and that of departure air traffic flow is in-between. The comparison results also show that the total and the arrival air traffic flows are insensitive to large fluctuations and dominated by small fluctuations, whereas the departure air traffic flow is insensitive to small fluctuations and dominated by large fluctuations. In addition, an investigation of multifractal characteristics of the time series during the thunderstorm season and the non-thunderstorm season reveals that the impact of the thunderstorm season on the total air traffic flow is the strongest, and there are significantly essential differences in the multifractality of the total air traffic flow before and after the thunderstorm season. For the arrival air traffic flow, there is only a difference in the extreme fluctuation rate, whereas there is no difference in essence for the departure air traffic flow, except for some quantity differences.

Suggested Citation

  • Zhang, Xie & Liu, Hongzhi & Zhao, Yifei & Zhang, Xingchen, 2019. "Multifractal detrended fluctuation analysis on air traffic flow time series: A single airport case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    • Handle: RePEc:eee:phsmap:v:531:y:2019:i:c:s0378437119310362
    DOI: 10.1016/j.physa.2019.121790
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    Citations

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    Cited by:

    1. Li, Jianhui & Li, Qiaozhi & Wang, Fang & Liu, Fan, 2022. "Hyperspectral redundancy detection and modeling with local Hurst exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    2. Telli, Şahin & Chen, Hongzhuan, 2020. "Multifractal behavior in return and volatility series of Bitcoin and gold in comparison," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Gui, Jun & Zheng, Zeyu & Fu, Dianzheng & Fu, Yang & Liu, Zhi, 2021. "Long-term correlations and multifractality of toll-free calls in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    4. Chandra, Aitichya & Verma, Ashish & Sooraj, K.P. & Padhi, Radhakant, 2023. "Modelling and assessment of the arrival and departure process at the terminal area: A case study of Chennai international airport," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    5. Santos, Fábio Sandro dos & Nascimento, Kerolly Kedma Felix do & Jale, Jader da Silva & Stosic, Tatijana & Marinho, Manoel H.N. & Ferreira, Tiago A.E., 2021. "Mixture distribution and multifractal analysis applied to wind speed in the Brazilian Northeast region," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    6. Vogl, Markus, 2023. "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framewo," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    7. Liu, Hongzhi & Zhang, Xie & Hu, Huaqing & Zhang, Xingchen, 2022. "Exploring the impact of flow values on multiscale complexity quantification of airport flight flow fluctuations," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    8. Chen, Yunxiang & Zhao, Yifei & Wu, Yexin, 2024. "Recent progress in air traffic flow management: A review," Journal of Air Transport Management, Elsevier, vol. 116(C).
    9. Sierra-Porta, D. & Domínguez-Monterroza, Andy-Rafael, 2022. "Linking cosmic ray intensities to cutoff rigidity through multifractal detrented fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    10. Olivares, Felipe & Sun, Xiaoqian & Wandelt, Sebastian & Zanin, Massimiliano, 2023. "Measuring landing independence and interactions using statistical physics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    11. Liu, Hongzhi & Zhang, Xingchen & Zhang, Xie, 2020. "Multiscale multifractal analysis on air traffic flow time series: A single airport departure flight case," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    12. Guan, Sihai & Wan, Dongyu & Yang, Yanmiao & Biswal, Bharat, 2022. "Sources of multifractality of the brain rs-fMRI signal," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    13. Telli, Şahin & Chen, Hongzhuan & Zhao, Xufeng, 2022. "Detecting multifractality and exposing distributions of local fluctuations: Detrended fluctuation analysis with descriptive statistics pooling," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    14. Olivares, Felipe & Zanin, Massimiliano, 2022. "Corrupted bifractal features in finite uncorrelated power-law distributed data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).

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