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Latent educational risks in maritime training: A hybrid Bayesian network SCBA case study
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DOI：10.1016/j.oceaneng.2026.127478.png)
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Abstract
En 中文
• Hybrid Fuzzy BT-BN model mitigates latent human errors in maritime operations. • SAM filters expert subjectivity to deduce probabilities under data scarcity. • Leaky Noisy-OR algorithm ensures scalability in complex Bayesian networks. • Infrastructural defects trigger most SCBA failures, not just operator error. • Modern simulation investments yield the highest risk reduction in maritime.
Keywords:
Maritime safety
Human reliability
Bayesian networks
Maritime education and training
Fuzzy logic
High-reliability organizations
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5.5K
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