Modelling of stochastic hybrid systems with applications to accident risk assessment

J. Krystul

Modelling of stochastic hybrid systems with applications to accident risk assessment

J. Krystul

Research output: Thesis › PhD Thesis - Research UT, graduation UT

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Abstract

Stochastic dynamical modelling of accident risk is of high interest for the safe design of complex safety-critical systems and operations, such as in nuclear and chemical industries, and advanced air traffic management. In comparison with statistical analysis of collected data, stochastic dynamical modelling approach has the advantage of enabling the use of stochastic analysis and advanced Monte Carlo simulation approaches.

Original language	English
Awarding Institution	University of Twente
Supervisors/Advisors	Bagchi, Arunabha, Supervisor
Thesis sponsors	European Commission project HYBRIDGE, IST-2001-32460.
Award date	6 Sept 2006
Place of Publication	Zutphen
Publisher	Wohrmann
Print ISBNs	90-365-2401-6
Publication status	Published - 6 Sept 2006

Keywords

EWI-9114
METIS-237921
CR-I.6
MSC-60J75
IR-57127

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title = "Modelling of stochastic hybrid systems with applications to accident risk assessment",

abstract = "Stochastic dynamical modelling of accident risk is of high interest for the safe design of complex safety-critical systems and operations, such as in nuclear and chemical industries, and advanced air traffic management. In comparison with statistical analysis of collected data, stochastic dynamical modelling approach has the advantage of enabling the use of stochastic analysis and advanced Monte Carlo simulation approaches.",

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AB - Stochastic dynamical modelling of accident risk is of high interest for the safe design of complex safety-critical systems and operations, such as in nuclear and chemical industries, and advanced air traffic management. In comparison with statistical analysis of collected data, stochastic dynamical modelling approach has the advantage of enabling the use of stochastic analysis and advanced Monte Carlo simulation approaches.

KW - EWI-9114

KW - METIS-237921

KW - CR-I.6

KW - MSC-60J75

KW - IR-57127

M3 - PhD Thesis - Research UT, graduation UT

SN - 90-365-2401-6

PB - Wohrmann

CY - Zutphen

ER -

Modelling of stochastic hybrid systems with applications to accident risk assessment

Abstract

Keywords

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