Dependence Assessment in Human Reliability Analysis Based on the Interval Evidential Reasoning Algorithm Under Interval Uncertainty
Dependence assessment, which is to assess the influence of the operator's failure of a task on the failure probability of subsequent tasks, is an important part in Human reliability analysis (HRA). The technique for human error rate prediction (THERP) has been widely applied to assess the depen...
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doaj-45191b91eac34f648264abf39ee7981d2021-03-30T04:29:34ZengIEEEIEEE Access2169-35362020-01-01822218722219810.1109/ACCESS.2020.30438489290015Dependence Assessment in Human Reliability Analysis Based on the Interval Evidential Reasoning Algorithm Under Interval UncertaintyWenhao Bi0https://orcid.org/0000-0002-3944-5395Fei Gao1https://orcid.org/0000-0002-9273-4559An Zhang2https://orcid.org/0000-0002-6085-9402Mi Yang3https://orcid.org/0000-0002-9856-575XSchool of Aeronautics, Northwestern Polytechnical University, Xi’an, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an, ChinaDependence assessment, which is to assess the influence of the operator's failure of a task on the failure probability of subsequent tasks, is an important part in Human reliability analysis (HRA). The technique for human error rate prediction (THERP) has been widely applied to assess the dependence in HRA. However, due to the complexity of the real world, various kinds of uncertainty could occur in dependence assessment problem, and how to properly express and deal with uncertainty especially interval uncertainty remains a pressing issue. In this article, a novel method based on the interval evidential reasoning (IER) algorithm is proposed to assess dependence in HRA under interval uncertainty. First, dependence influential factors are identified and their functional relationship is determined. Then, judgments on these factors provided by the analysts are represented using interval belief distributions. Next, the interval evidential reasoning algorithm is employed to aggregate interval belief distributions of different factors according to their functional relationship while considering the credibility of the interval belief distribution. Finally, the conditional human error probability (CHEP) is calculated based on the fused interval belief distribution, where the upper and lower values are determined by assigning belief degree to the highest and lowest grade of the corresponding grade interval, respectively. Two numerical examples demonstrate that the proposed method not only properly deals with interval uncertainty using interval belief distribution and IER algorithm, but also provides a novel and effective way for dependence assessment in HRA.https://ieeexplore.ieee.org/document/9290015/Dependence assessmenthuman reliability analysisinterval evidential reasoninginterval uncertainty |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wenhao Bi Fei Gao An Zhang Mi Yang |
spellingShingle |
Wenhao Bi Fei Gao An Zhang Mi Yang Dependence Assessment in Human Reliability Analysis Based on the Interval Evidential Reasoning Algorithm Under Interval Uncertainty IEEE Access Dependence assessment human reliability analysis interval evidential reasoning interval uncertainty |
author_facet |
Wenhao Bi Fei Gao An Zhang Mi Yang |
author_sort |
Wenhao Bi |
title |
Dependence Assessment in Human Reliability Analysis Based on the Interval Evidential Reasoning Algorithm Under Interval Uncertainty |
title_short |
Dependence Assessment in Human Reliability Analysis Based on the Interval Evidential Reasoning Algorithm Under Interval Uncertainty |
title_full |
Dependence Assessment in Human Reliability Analysis Based on the Interval Evidential Reasoning Algorithm Under Interval Uncertainty |
title_fullStr |
Dependence Assessment in Human Reliability Analysis Based on the Interval Evidential Reasoning Algorithm Under Interval Uncertainty |
title_full_unstemmed |
Dependence Assessment in Human Reliability Analysis Based on the Interval Evidential Reasoning Algorithm Under Interval Uncertainty |
title_sort |
dependence assessment in human reliability analysis based on the interval evidential reasoning algorithm under interval uncertainty |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Dependence assessment, which is to assess the influence of the operator's failure of a task on the failure probability of subsequent tasks, is an important part in Human reliability analysis (HRA). The technique for human error rate prediction (THERP) has been widely applied to assess the dependence in HRA. However, due to the complexity of the real world, various kinds of uncertainty could occur in dependence assessment problem, and how to properly express and deal with uncertainty especially interval uncertainty remains a pressing issue. In this article, a novel method based on the interval evidential reasoning (IER) algorithm is proposed to assess dependence in HRA under interval uncertainty. First, dependence influential factors are identified and their functional relationship is determined. Then, judgments on these factors provided by the analysts are represented using interval belief distributions. Next, the interval evidential reasoning algorithm is employed to aggregate interval belief distributions of different factors according to their functional relationship while considering the credibility of the interval belief distribution. Finally, the conditional human error probability (CHEP) is calculated based on the fused interval belief distribution, where the upper and lower values are determined by assigning belief degree to the highest and lowest grade of the corresponding grade interval, respectively. Two numerical examples demonstrate that the proposed method not only properly deals with interval uncertainty using interval belief distribution and IER algorithm, but also provides a novel and effective way for dependence assessment in HRA. |
topic |
Dependence assessment human reliability analysis interval evidential reasoning interval uncertainty |
url |
https://ieeexplore.ieee.org/document/9290015/ |
work_keys_str_mv |
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