基于概率语言环境下达成共识过程的人类可靠性分析集成 CREAM

IF 2.3 4区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Systems Pub Date : 2024-07-10 DOI:10.3390/systems12070249
Xue-Guo Xu, Ling Zhang, Si-Xuan Wang, Hua-Ping Gong, Hu-Chen Liu
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引用次数: 0

摘要

人为可靠性分析(HRA)被广泛用于评估人为错误对各种复杂人机系统的影响,以提高其安全性和可靠性。然而,由于状态评估信息的不确定性和常见性能条件(CPC)之间的复杂关系,现实中很难估算人为错误概率(HEP)。本文旨在提出一种新的认知可靠性和误差综合分析方法(CREAM),以解决概率语言环境下的人为错误概率问题。首先,利用概率语言术语集(PLTS)来处理专家提供的不确定任务状态评估。其次,采用最小冲突共识模型(MCCM)处理冲突任务状态评估信息,帮助专家达成共识。第三,采用熵权法确定 CPC 的相对目标权重。此外,还引入了 CPC 效果指数,以评估 CPC 对性能可靠性的整体影响,并获得 HEP 估计值。最后,通过一个医疗保健实际案例证明了所提出的 CREAM 的可靠性。结果表明,新的集成 CREAM 不仅能有效代表专家的不确定任务状态评估,还能在 HRA 中确定更可靠的 HEP 估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Integrated CREAM for Human Reliability Analysis Based on Consensus Reaching Process under Probabilistic Linguistic Environment
Human reliability analysis (HRA) is widely used to evaluate the impact of human errors on various complex human–machine systems for enhancing their safety and reliability. Nevertheless, it is hard to estimate the human error probability (HEP) in reality due to the uncertainty of state assessment information and the complex relations among common performance conditions (CPCs). In this paper, we aim to present a new integrated cognitive reliability and error analysis method (CREAM) to solve the HRA problems under probabilistic linguistic environment. First, the probabilistic linguistic term sets (PLTSs) are utilized to handle the uncertain task state assessments provided by experts. Second, the minimum conflict consensus model (MCCM) is employed to deal with conflict task state assessment information to assist experts reach consensus. Third, the entropy weighting method is used to determine the relative objective weights of CPCs. Additionally, the CPC effect indexes are introduced to assess the overall effect of CPCs on performance reliability and obtain the HEP estimation. Finally, the reliability of the proposed CREAM is demonstrated via a healthcare practical case. The result shows that the new integrated CREAM can not only effectively represent experts’ uncertain task state assessments but also determine more reliable HEP estimation in HRA.
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来源期刊
Systems
Systems Decision Sciences-Information Systems and Management
CiteScore
2.80
自引率
15.80%
发文量
204
审稿时长
11 weeks
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