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New method for dependence assessment in human reliability analysis based on linguistic hesitant fuzzy information

  • Zhang, Ling (School of Management, Shanghai University) ;
  • Zhu, Yu-Jie (School of Management, Shanghai University) ;
  • Hou, Lin-Xiu (School of Management, Shanghai University) ;
  • Liu, Hu-Chen (College of Economics and Management, China Jiliang University)
  • Received : 2021.03.23
  • Accepted : 2021.05.10
  • Published : 2021.11.25

Abstract

Human reliability analysis (HRA) is a proactive approach to model and evaluate human systematic errors, and has been extensively applied in various complicated systems. Dependence assessment among human errors plays a key role in the HRA, which relies heavily on the knowledge and experience of experts in real-world cases. Moreover, there are ofthen different types of uncertainty when experts use linguistic labels to evaluate the dependencies between human failure events. In this context, this paper aims to develop a new method based on linguistic hesitant fuzzy sets and the technique for human error rate prediction (THERP) technique to manage the dependence in HRA. This method handles the linguistic assessments given by experts according to the linguistic hesitant fuzzy sets, determines the weights of influential factors by an extended best-worst method, and confirms the degree of dependence between successive actions based on the THERP method. Finally, the effectiveness and practicality of the presented linguistic hesitant fuzzy THERP method are demonstrated through an empirical healthcare dependence analysis.

Keywords

Acknowledgement

The authors are very grateful to the respected editor and the anonymous referees for their insightful and constructive comments, which helped to improve the overall quality of the paper. This study was supported by the major project of the National Social Science Foundation of China (No. 21ZDA024).

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