IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v41y2009i3p1520-1530.html
   My bibliography  Save this article

Using fractal dimension to quantify long-range persistence in global solar radiation

Author

Listed:
  • Harrouni, S.
  • Guessoum, A.

Abstract

The basic characteristic of a self-affine time series is that the persistence (or long-term memory) is scale invariant and long-range. The persistence measures the correlation between adjacent values within the time series. Values of a time series can affect other values in the time series that are not only nearby in time but also far away in time. A number of statistical approaches are currently in use to quantify persistence in time series. In this paper, we examine the persistence of daily and annually global solar irradiation data with many years of record using the fractal dimension. For this purpose, a new method to measure the fractal dimension of temporal discrete signals is presented. The fractal dimension is then used as criterion in an approach we have elaborated to detect the long-term correlation in solar irradiation series. The results show that daily and annual solar irradiations are anti-persistent.

Suggested Citation

  • Harrouni, S. & Guessoum, A., 2009. "Using fractal dimension to quantify long-range persistence in global solar radiation," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1520-1530.
    • Handle: RePEc:eee:chsofr:v:41:y:2009:i:3:p:1520-1530
    DOI: 10.1016/j.chaos.2008.06.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096007790800283X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2008.06.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Havlin, S. & Buldyrev, S.V. & Bunde, A. & Goldberger, A.L. & Ivanov, P.Ch. & Peng, C.-K. & Stanley, H.E., 1999. "Scaling in nature: from DNA through heartbeats to weather," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 273(1), pages 46-69.
    2. Iwashita, Yukinori & Nakanishi, Ichiro, 2005. "Scaling laws of earthquakes derived by renormalization group method," Chaos, Solitons & Fractals, Elsevier, vol. 24(2), pages 511-518.
    3. Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and market structure," Chaos, Solitons & Fractals, Elsevier, vol. 31(4), pages 995-1000.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chang, Tian-Pau & Ko, Hong-Hsi & Liu, Feng-Jiao & Chen, Pai-Hsun & Chang, Ying-Pin & Liang, Ying-Hsin & Jang, Horng-Yuan & Lin, Tsung-Chi & Chen, Yi-Hwa, 2012. "Fractal dimension of wind speed time series," Applied Energy, Elsevier, vol. 93(C), pages 742-749.
    2. Tsekouras, Georgios & Koutsoyiannis, Demetris, 2014. "Stochastic analysis and simulation of hydrometeorological processes associated with wind and solar energy," Renewable Energy, Elsevier, vol. 63(C), pages 624-633.
    3. dos Anjos, Priscilla Sales & da Silva, Antonio Samuel Alves & Stošić, Borko & Stošić, Tatijana, 2015. "Long-term correlations and cross-correlations in wind speed and solar radiation temporal series from Fernando de Noronha Island, Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 90-96.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Telesca, Luciano & Song, Weiguo, 2011. "Time-scaling properties of city fires," Chaos, Solitons & Fractals, Elsevier, vol. 44(7), pages 558-568.
    2. Wang, Xiao-Tian & Zhu, En-Hui & Tang, Ming-Ming & Yan, Hai-Gang, 2010. "Scaling and long-range dependence in option pricing II: Pricing European option with transaction costs under the mixed Brownian–fractional Brownian model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 445-451.
    3. Chen, Yanguang & Zhou, Yixing, 2008. "Scaling laws and indications of self-organized criticality in urban systems," Chaos, Solitons & Fractals, Elsevier, vol. 35(1), pages 85-98.
    4. Pavlos, G.P. & Karakatsanis, L.P. & Iliopoulos, A.C. & Pavlos, E.G. & Xenakis, M.N. & Clark, Peter & Duke, Jamie & Monos, D.S., 2015. "Measuring complexity, nonextensivity and chaos in the DNA sequence of the Major Histocompatibility Complex," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 188-209.
    5. Cun Chen & Shaokang Guan & Liying Zhang, 2018. "Complex Dynamical Behavior in the Shear-Displacement Model for Bulk Metallic Glasses during Plastic Deformation," Complexity, Hindawi, vol. 2018, pages 1-13, December.
    6. Cajueiro, Daniel O. & Tabak, Benjamin M., 2009. "Testing for long-range dependence in the Brazilian term structure of interest rates," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1559-1573.
    7. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Long memory volatility in Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1425-1433.
    8. Batten, Jonathan A. & Ellis, Craig A. & Fethertson, Thomas A., 2008. "Sample period selection and long-term dependence: New evidence from the Dow Jones index," Chaos, Solitons & Fractals, Elsevier, vol. 36(5), pages 1126-1140.
    9. Lei, Yadong & Zhang, Feng & Miao, Lijuan & Yu, Qiu-Run & Duan, Mingkeng & Fraedrich, Klaus & Yu, Zifeng, 2020. "Potential impacts of future reduced aerosols on internal dynamics characteristics of precipitation based on model simulations over southern China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    10. Takami, Marcelo Yoshio & Tabak, Benjamin Miranda, 2008. "Interest rate option pricing and volatility forecasting: An application to Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 38(3), pages 755-763.
    11. Yuan, Naiming & Fu, Zuntao & Mao, Jiangyu, 2010. "Different scaling behaviors in daily temperature records over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(19), pages 4087-4095.
    12. Liu, Li, 2014. "Cross-correlations between crude oil and agricultural commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 293-302.
    13. A. Sensoy & Benjamin M. Tabak, 2013. "How much random does European Union walk? A time-varying long memory analysis," Working Papers Series 342, Central Bank of Brazil, Research Department.
    14. Cajueiro, Daniel O. & Tabak, Benjamin M., 2008. "Testing for time-varying long-range dependence in real state equity returns," Chaos, Solitons & Fractals, Elsevier, vol. 38(1), pages 293-307.
    15. Sensoy, A., 2013. "Time-varying long range dependence in market returns of FEAS members," Chaos, Solitons & Fractals, Elsevier, vol. 53(C), pages 39-45.
    16. Foad Shokrollahi, 2017. "The valuation of European option with transaction costs by mixed fractional Merton model," Papers 1702.00152, arXiv.org.
    17. Sensoy, A., 2013. "Effects of monetary policy on the long memory in interest rates: Evidence from an emerging market," Chaos, Solitons & Fractals, Elsevier, vol. 57(C), pages 85-88.
    18. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Contemporaneous aggregation and long-memory property of returns and volatility in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4844-4854.
    19. Jonathan A. Batten & Cetin Ciner & Brian M. Lucey & Peter G. Szilagyi, 2013. "The structure of gold and silver spread returns," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 561-570, March.
    20. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:41:y:2009:i:3:p:1520-1530. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.