Konferenzbeitrag

Statistical Analysis of Wind Speed for the Probability Evaluation of Cancelled Departure for Catamarans and Ferries

Weather data bases are important in optimizing a range of economic activities, such as maritime traffic. In this paper, a statistical analysis of data has been carried out, which includes the interpretation of the results with an emphasis on the analysis of consequences for local population. The proposed procedure is supported by realistic data for wind speed and direction measured at meteorological station Split in the period from 2002 to 2011. Using available data, the annual as well as seasonal wind roses for the specified location are shown. Furthermore, wind speed data are approximated by the Weibull's probability distribution that enables estimating the probability of exceeding a particular wind speed, i.e. Beaufort number for this location. Thus, the probability of cancelled departure for catamarans, as well as ferries from the Split city port is determined for the annual level as well as for each season. The obtained results provide a more detailed insight into the important occurrence of cancelled departure of catamarans and ferries, significant for the lives of the islanders gravitating to Split.

Sprache
Englisch

Erschienen in
In: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Dubrovnik, Croatia, 7-9 September 2017 ; Year: 2017 ; Pages: 340-350 ; Zagreb: IRENET - Society for Advancing Innovation and Research in Economy

Klassifikation
Wirtschaft
Statistical Simulation Methods: General
Thema
knowledge
information quality
applied statistics
probability estimation
wind
weibull distribution

Ereignis
Geistige Schöpfung
(wer)
Degiuli, Nastia
Runje, Biserka
Farkas, Andrea
Ereignis
Veröffentlichung
(wer)
IRENET - Society for Advancing Innovation and Research in Economy
(wo)
Zagreb
(wann)
2017

Handle
Letzte Aktualisierung
10.03.2025, 11:41 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Konferenzbeitrag

Beteiligte

  • Degiuli, Nastia
  • Runje, Biserka
  • Farkas, Andrea
  • IRENET - Society for Advancing Innovation and Research in Economy

Entstanden

  • 2017

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