Multiparametric statistical and dynamical analysis of angular high-frequency wind speed time series

被引:5
|
作者
Stosic, Tatijana [1 ]
Telesca, Luciano [2 ]
Stosic, Borko [1 ]
机构
[1] Univ Fed Rural Pernambuco, Dept Estat & Informat, Rua Dom Manoel de Medeiros S-N, BR-52171900 Recife, PE, Brazil
[2] CNR, Inst Methodol Environm Anal Cda S Loja, I-85050 Tito, Italy
关键词
Wind speed; Persistence dynamics; Detrended fluctuation analysis; Multifractal detrended fluctuation analysis; Fisher-Shannon analysis; LONG-TERM CORRELATIONS; FISHER INFORMATION; DISTRIBUTIONS; COMPLEXITY; RECORDS;
D O I
10.1016/j.physa.2020.125627
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
High frequency data from the city of Petrolina, Northeast Brazil, are used to find the wind speed projection series at different angles, which are then analyzed by using several statistical tools: detrended fluctuation analysis (DFA), multifractal detrended fluctuation analysis (MFDFA) and Fisher-Shannon analysis (FSA). It is found that alpha, the DFA scaling exponent, varies between 0.6 (indicating weak persistence) and unity (strong persistence), at different time frames and at different projection angles. At lower projection angles wind speed is characterized by higher heterogeneity, lower disorder, higher organization and relative dominance of small fluctuations. The statistical analysis of wind speed with varying the direction could contribute to enrich the knowledge of the dynamics of wind speed. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Fisher-Shannon Complexity Analysis of High-Frequency Urban Wind Speed Time Series
    Guignard, Fabian
    Mauree, Dasaraden
    Lovallo, Michele
    Kanevski, Mikhail
    Telesca, Luciano
    ENTROPY, 2019, 21 (01)
  • [2] Extreme Value Analysis of Multivariate High-Frequency Wind Speed Data
    Steinkohl, Christina
    Davis, Richard A.
    Klueppelberg, Claudia
    JOURNAL OF STATISTICAL THEORY AND PRACTICE, 2013, 7 (01) : 73 - 94
  • [3] Wavelet variance scale-dependence as a dynamics discriminating tool in high-frequency urban wind speed time series
    Guignard, Fabian
    Mauree, Dasaraden
    Kanevski, Mikhail
    Telesca, Luciano
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2019, 525 : 771 - 777
  • [4] Machine Learning Techniques for Anomaly Detection in High-Frequency Time Series of Wind Speed and Greenhouse Gas Concentration Measurements
    A. J. Kasatkin
    M. A. Krinitskiy
    Moscow University Physics Bulletin, 2023, 78 : S138 - S148
  • [5] Machine Learning Techniques for Anomaly Detection in High-Frequency Time Series of Wind Speed and Greenhouse Gas Concentration Measurements
    Kasatkin, A. J.
    Krinitskiy, M. A.
    MOSCOW UNIVERSITY PHYSICS BULLETIN, 2023, 78 (SUPPL 1) : S138 - S148
  • [6] Dynamical analysis of time series by statistical tests
    Deco, G
    Schittenkopf, C
    Schurmann, B
    INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 1997, 7 (12): : 2629 - 2652
  • [7] Dynamical models of high-frequency data analysis
    Lim, Gyuchang
    Kim, Soo Yoo
    Kang, Ji-Hyun
    Kim, Kyungsik
    COMPUTER PHYSICS COMMUNICATIONS, 2007, 177 (1-2) : 187 - 187
  • [8] Cluster Analysis of High-Dimensional High-Frequency Financial Time Series
    Pasha, Syed A.
    Leong, Philip H. W.
    PROCEEDINGS OF THE 2013 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE FOR FINANCIAL ENGINEERING & ECONOMICS (CIFER), 2013, : 74 - 81
  • [9] Modelling high-frequency economic time series
    Tang, LH
    Huang, ZF
    PHYSICA A, 2000, 288 (1-4): : 444 - 450
  • [10] On the predictability of high-frequency financial time series
    Tanaka-Yamawaki, M
    KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS, 2003, 2773 : 1100 - 1108