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Multivariate multifractal detrended fluctuation analysis of 3D wind field signals

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  • Zhang, Xiaonei
  • Zeng, Ming
  • Meng, Qinghao

Abstract

Characterizing the dynamic behavior underlying wind field from experimental multivariate signals is a challenging problem of continuous interest. In this work, we propose the multivariate multifractal detrended fluctuation analysis (MV-MFDFA) method to directly study the fractal dynamics of multichannel data in a complex system. By conducting several simulations on synthetic multivariate series, the validity of the proposed MV-MFDFA is illustrated. Then we utilize MV-MFDFA to analyze the 3D wind field signals collected at two different airflow environments, i.e., indoor and outdoor environments. Results show that the indoor and outdoor three wind vectors show multifractal properties, and the multifractal degrees of outdoor three wind vectors are stronger than those of corresponding indoor three wind vectors. By analyzing the indoor and outdoor multivariate wind speed, we find that the indoor and outdoor multivariate wind speed are antipersistent long-range correlation, and the indoor multivariate wind speed exhibits weaker multifractal properties than that of outdoor multivariate wind speed. Moreover, the multifractality of indoor multivariate wind speed depends mainly on the large fluctuations, while the multifractality of outdoor multivariate wind speed depends mainly on the small fluctuations. These findings indicate that the MV-MFDFA allows better understanding the dynamical mechanisms governing 3D wind variability.

Suggested Citation

  • Zhang, Xiaonei & Zeng, Ming & Meng, Qinghao, 2018. "Multivariate multifractal detrended fluctuation analysis of 3D wind field signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 513-523.
    • Handle: RePEc:eee:phsmap:v:490:y:2018:i:c:p:513-523
    DOI: 10.1016/j.physa.2017.08.073
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    1. Pimenta, Felipe & Kempton, Willett & Garvine, Richard, 2008. "Combining meteorological stations and satellite data to evaluate the offshore wind power resource of Southeastern Brazil," Renewable Energy, Elsevier, vol. 33(11), pages 2375-2387.
    2. Kavasseri, Rajesh G. & Nagarajan, Radhakrishnan, 2005. "A multifractal description of wind speed records," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 165-173.
    3. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    4. Telesca, Luciano & Toth, Laszlo, 2016. "Multifractal detrended fluctuation analysis of Pannonian earthquake magnitude series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 21-29.
    5. Gu, Rongbao & Chen, Hongtao & Wang, Yudong, 2010. "Multifractal analysis on international crude oil markets based on the multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(14), pages 2805-2815.
    6. Shang, Pengjian & Lu, Yongbo & Kamae, Santi, 2008. "Detecting long-range correlations of traffic time series with multifractal detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 36(1), pages 82-90.
    7. Kaushik Matia & Yosef Ashkenazy & H. Eugene Stanley, 2003. "Multifractal Properties of Price Fluctuations of Stocks and Commodities," Papers cond-mat/0308012, arXiv.org.
    8. Telesca, Luciano & Lovallo, Michele & Kanevski, Mikhail, 2016. "Power spectrum and multifractal detrended fluctuation analysis of high-frequency wind measurements in mountainous regions," Applied Energy, Elsevier, vol. 162(C), pages 1052-1061.
    9. Telesca, Luciano & Lovallo, Michele & Lapenna, Vincenzo & Macchiato, Maria, 2007. "Long-range correlations in two-dimensional spatio-temporal seismic fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 279-284.
    10. Mohandes, M.A. & Halawani, T.O. & Rehman, S. & Hussain, Ahmed A., 2004. "Support vector machines for wind speed prediction," Renewable Energy, Elsevier, vol. 29(6), pages 939-947.
    11. Tascikaraoglu, Akin & Sanandaji, Borhan M. & Poolla, Kameshwar & Varaiya, Pravin, 2016. "Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform," Applied Energy, Elsevier, vol. 165(C), pages 735-747.
    12. Podobnik, Boris & Horvatic, Davor & Lam Ng, Alfonso & Eugene Stanley, H. & Ivanov, Plamen Ch., 2008. "Modeling long-range cross-correlations in two-component ARFIMA and FIARCH processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3954-3959.
    13. Rehman, Shafiqur & Halawani, Talal Omar, 1994. "Statistical characteristics of wind in Saudi Arabia," Renewable Energy, Elsevier, vol. 4(8), pages 949-956.
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    2. Wang, Fang & Han, Guosheng, 2023. "Coupling correlation adaptive detrended analysis for multiple nonstationary series," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    3. Nava, Noemi & Di Matteo, T. & Aste, Tomaso, 2018. "Dynamic correlations at different time-scales with empirical mode decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 534-544.
    4. Meo, Marcos M. & Iaconis, Francisco R. & Del Punta, Jessica A. & Delrieux, Claudio A. & Gasaneo, Gustavo, 2024. "Multifractal information on reading eye tracking data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 638(C).
    5. Li, Shuping & Li, Jianfeng & Lu, Xinsheng & Sun, Yihong, 2022. "Exploring the dynamic nonlinear relationship between crude oil price and implied volatility indices: A new perspective from MMV-MFDFA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    6. Milena Kojić & Petar Mitić & Marko Dimovski & Jelena Minović, 2021. "Multivariate Multifractal Detrending Moving Average Analysis of Air Pollutants," Mathematics, MDPI, vol. 9(7), pages 1-17, March.

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