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SAFETY RISK ASSESSMENT USING BAYESIAN BELIEF NETWORK

Abstract

The solution of the problem of modelling and quantitative assessment of flight safety risk is being considered in this paper. The article considers the main groups of mathematical models used to quantify the risks of flight safety, which can be used by providers of aviation services. The authors demonstrate and discuss risk modeling possibilities in the field of flight safety on the basis of Bayesian belief networks.In this paper a mathematical model is built on the basis of identified hazards, and this model allows to determine the level of risk for each hazard and the consequences of their occurrence using Bayesian belief networks, consisting of marginal probability distributions graph and conditional probability tables. This mathematical model allows to determine the following, based on the data on adverse events and hazard identification: the probability of various adverse events in all dangers occurrence, the risk level for each of the identified hazards, the most likely consequences of the given danger oc- currence. For risk modeling in the field of flight safety on the basis of Bayesian belief networks there were used supple- mentary Bayes Net Toolbox for MATLAB with open source. To determine the level of risk in the form specified in ICAO Doc 9859 "Flight Safety Management Manual" of the International Civil Aviation Organization, the authors wrote a func- tion to MATLAB, allowing each pair of probability - to set severity level in line with alphanumeric value and significance of the risk category.Risk model in the field of flight safety on the basis of Bayesian belief networks corresponds to the definition of risk by Kaplan and Garrick. The advantage of the developed risk assessment method over other methods is shown in the paper.

About the Authors

V. M. Rukhlinskiy
The Interstate Aviation Committee
Russian Federation

Doctor of Technical Sciences, Chairman of the Commission for Relations with ICAO Board, International and Interstate Organizations,

Moscow



A. A. Khaustov
Rossiya airlines JSC
Russian Federation

Head of Analysis and Risk Management Section of the Safety Management Department,

Moscow



A. S. Molotovnik
Rossiya airlines JSC
Russian Federation

Chief Specialist of Analysis and Risk Management Section of the Safety Management Department, 

Moscow



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For citations:


Rukhlinskiy V.M., Khaustov A.A., Molotovnik A.S. SAFETY RISK ASSESSMENT USING BAYESIAN BELIEF NETWORK. Civil Aviation High Technologies. 2017;20(3):76-89. (In Russ.)

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ISSN 2079-0619 (Print)
ISSN 2542-0119 (Online)