Research on Human Error Risk Evaluation Using Extended Bayesian Networks with Hybrid Data

Xing Pan, Dujun Zuo, Wenjin Zhang, Lunhu Hu, Huixiong Wang and Jing Jiang

Reliability Engineering and System Safety, 2021, vol. 209, issue C

Abstract: Bayesian networks (BNs) play an important role in performing uncertainty analysis. BNs, as a sort of directed acyclic graph with probabilities, can establish causality and clarify complex uncertain relationships to benefit risk analyze. A large number of accurate data must be obtained for precisely reasoning, but it is often difficult in human reliability analysis (HRA). Inadequate data on space launch sites make it necessary to utilize different types of data in engineering. This paper studies the uncertainty in BNs and classifies the using data. Besides, the concept of Extended BNs containing the most likely probabilities and probability boundaries is proposed to address the hybrid data problem in BNs. Accordingly, the mathematical model and usage of the Extended BNs are also developed to fuse different types of data in HRA. To verify the rationality and accuracy of this method, the Extended BN with hybrid data is applied to HRA for fueling task in space launch sites. Finally, the case study shows the validity of the uncertainty expression in Extended BNs, and the Extended BNs perform well in risk prediction and risk avoidance.

Keywords: Bayesian Network; Human Reliability Analysis; Hybrid Data (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:209:y:2021:i:c:s0951832020308280

DOI: 10.1016/j.ress.2020.107336

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