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Taxonomy of correlations of wind velocity — an application to the Sicilian area

Author

Listed:
  • Bivona, S.
  • Bonanno, G.
  • Burlon, R.
  • Gurrera, D.
  • Leone, C.

Abstract

We present an algorithm that allows us to analyze the cross-correlation of wind velocity measured in different locations; this algorithm is applied to 29 recording stations in Sicily. The results show that such correlations present a significant and persistent ultrametric structure that is influenced by the geographical neighborhood as well as by the presence of mountain and the sea. The algorithm presented, that is also able to reveal weak correlations, can be used as a starting point for the development of multivariate models of wind.

Suggested Citation

  • Bivona, S. & Bonanno, G. & Burlon, R. & Gurrera, D. & Leone, C., 2008. "Taxonomy of correlations of wind velocity — an application to the Sicilian area," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5910-5915.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:23:p:5910-5915
    DOI: 10.1016/j.physa.2008.06.026
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    Cited by:

    1. Kantar, Ersin & Keskin, Mustafa, 2013. "The relationships between electricity consumption and GDP in Asian countries, using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5678-5684.
    2. Kazemilari, Mansooreh & Mardani, Abbas & Streimikiene, Dalia & Zavadskas, Edmundas Kazimieras, 2017. "An overview of renewable energy companies in stock exchange: Evidence from minimal spanning tree approach," Renewable Energy, Elsevier, vol. 102(PA), pages 107-117.
    3. Kantar, Ersin & Aslan, Alper & Deviren, Bayram & Keskin, Mustafa, 2016. "Hierarchical structure of the countries based on electricity consumption and economic growth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 454(C), pages 1-10.

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    Keywords

    Wind; Correlation; Taxonomy;
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