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A hybrid fuzzy system dynamics approach for risk analysis of AUV operations

Loh, TY ORCID: 0000-0001-6484-5254, Brito, MP, Bose, N, Xu, J, Nikolova, N ORCID: 0000-0001-6160-6282 and Tenekedjiev, K ORCID: 0000-0003-3549-0671 2020 , 'A hybrid fuzzy system dynamics approach for risk analysis of AUV operations' , Journal of Advanced Computational Intelligence and Intelligent Informatics, vol. 24, no. 1 , pp. 1-14 , doi: 10.20965/jaciii.2020.p0026.

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The maturing of autonomous technology has fostered a rapid expansion in the use of Autonomous Underwater Vehicles (AUVs). To prevent the loss of AUVs during deployments, existing risk analysis approaches tend to focus on technicalities, historical data and experts’ opinion for probability quantification. However, data may not always be available and the complex interrelationships between risk factors are often neglected due to uncertainties. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. The approach utilises the strengths while overcoming limitations of both systemdynamics and fuzzy set theory. Presented as a threestep iterative framework, the approach was applied on a case study to examine the impact of crew operating experience on the risk of AUV loss. Results showed not only that initial experience of the team affects the risk of loss, but any loss of experience in earlier stages of the AUV program have a lesser impact as compared to later stages. A series of risk control policies were recommended based on the results. The case study demonstrated how the FuSDRA approach can be applied to inform human resource and risk management strategies, or broader application within the AUV domain and other complex technological systems.

Item Type: Article
Authors/Creators:Loh, TY and Brito, MP and Bose, N and Xu, J and Nikolova, N and Tenekedjiev, K
Keywords: AUV, risk management, fuzzy logic, simulation
Journal or Publication Title: Journal of Advanced Computational Intelligence and Intelligent Informatics
Publisher: Fuji Technology Press Ltd.
ISSN: 1343-0130
DOI / ID Number: 10.20965/jaciii.2020.p0026
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Copyright © 2020 Fuji Technology Press Ltd.

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