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Monte Carlo simulation of climate-weather change process at maritime ferry operating area

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Języki publikacji
EN
Abstrakty
EN
The paper presents a computer simulation technique applied to generating the climate-weather change process at Baltic Sea restricted waters and its characteristics evaluation. The Monte Carlo method is used under the assumption of semi-Markov model of this process. A procedure and an algorithm of climate-weather change process’ realizations generating and its characteristics evaluation are proposed to be applied in C# program preparation. Using this program, the climate-weather change process’ characteristics are predicted for the maritime ferry operating area. Namely, the mean values and standard deviations of the unconditional sojourn times, the limit values of transient probabilities and the mean values of total sojourn times for the fixed time at the climate-weather states are determined.
Twórcy
  • Katedra Matematyki, Akademia Morska, ul. Morska 83, 81-225 Gdynia
Bibliografia
  • GRABSKI F., JAŹWIŃSKI J. 2009. Funkcje o losowych argumentach w zagadnieniach niezawodności, bezpieczeństwa i logistyki. Wydawnictwa Komunikacji i Łączności, Warszawa.
  • GRABSKI F. 2014. Semi-Markov Processes: Applications in System Reliability and Maintenance. Elsevier.
  • KOŁOWROCKI K. 2004. Reliability of Large Systems. Elsevier.
  • KOŁOWROCKI K. 2014. Reliability of Large and Complex Systems. Elsevier.
  • KOŁOWROCKI K., KULIGOWSKA E. 2013. Monte Carlo simulation application to reliability evaluation of port grain transportation system operating at variable conditions. Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars, 4(1): 73–81.
  • KOŁOWROCKI K., KULIGOWSKA E., SOSZYŃSKA-BUDNY J. 2013. Monte Carlo simulation for optimization of object operation process and reliability. Journal of KONBiN, 24(4): 79–92.
  • KOŁOWROCKI K., KULIGOWSKA E., SOSZYŃSKA-BUDNY J., TORBICKI M. 2017. Simplified Impact Model of Critical Infrastructure Safety Related to Climate-Weather Change Process. Slovak Computer Sciences and Informatics Journal, 1: 187–190.
  • KOŁOWROCKI K., SOSZYŃSKA-BUDNY J. 2011. Reliability and Safety of Complex Systems and Processes: Modeling – Identification – Prediction – Optimization. Springer.
  • KOŁOWROCKI K., SOSZYŃSKA-BUDNY J. 2016a. Modelling climate-weather change process including extreme weather hazards for critical infrastructure operating area. Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars, 7(3): 149–154.
  • KOŁOWROCKI K., SOSZYŃSKA-BUDNY J. 2016b. Prediction of climate-weather change process for port oil piping transportation system and maritime ferry operating at Baltic Sea area. Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars, 7(3): 143–148.
  • KULIGOWSKA E. 2017. Identification and prediction of climate-weather change process for maritime ferry operating area. Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars, 8(2): 129–134.
  • KULIGOWSKA E., TORBICKI M. 2017. Critical infrastructure integrated safety model related to climateweather change process application to port oil piping transportation system operating at land Baltic seaside area. 27th ESREL Conference Proceedings, European Safety and Reliability Conference 2017, Portoroz, Slovenia, to appear.
  • KROESE D.P., TAIMRE T., BOTEV Z.I. 2011. Handbook of Monte Carlo Methods. John Willey & Sons, Inc., Hoboken, New Jersey.
  • LIMNIOS N., OPRISAN G. 2005. Semi-Markov Processes and Reliability. Birkhauser, Boston.
  • MARSAGLIA G., TSANG W.W. 2000. The Ziggurat Method for Generating Random Variables. Journal of Statistical Software, 5(8).
  • ZIO E., MARSEGUERRA M. 2002. Basics of the Monte Carlo Method with Application to System Reliability. LiLoLe.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e0a1f0c2-d3c7-49c7-a65a-ffce39e2c40d
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