title: Dependence Assessment in Human Reliability Analysis Using Evidence Theory and AHP.
abstract: Dependence assessment among human errors in human reliability analysis (HRA) is an important issue. Many of the dependence assessment methods in HRA rely heavily on the expert's opinion, thus are subjective and may sometimes cause inconsistency. In this article, we propose a computational model based on the Dempster-Shafer evidence theory (DSET) and the analytic hierarchy process (AHP) method to handle dependence in HRA. First, dependence influencing factors among human tasks are identified and the weights of the factors are determined by experts using the AHP method. Second, judgment on each factor is given by the analyst referring to anchors and linguistic labels. Third, the judgments are represented as basic belief assignments (BBAs) and are integrated into a fused BBA by weighted average combination in DSET. Finally, the CHEP is calculated based on the fused BBA. The proposed model can deal with ambiguity and the degree of confidence in the judgments, and is able to reduce the subjectivity and improve the consistency in the evaluation process.
authors.affiliation: School of Automation Engineering, Shanghai University of Electric Power, Shanghai, 200090, China.
authors.forename: Xiaoyan
authors.initials: X
authors.lastname: Su
authors.affiliation: School of Engineering, Vanderbilt University, Nashville, TN, USA.
authors.forename: Sankaran
authors.initials: S
authors.lastname: Mahadevan
authors.affiliation: School of Electronics and Information Technology, Shanghai Jiao Tong University, Shanghai, 200240, China.
authors.forename: Peida
authors.initials: P
authors.lastname: Xu
authors.affiliation: School of Computer and Information Science, Southwest University, Chongqing, 400715, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: Deng
mesh_terms: D006801:Humans; D008962:Models, Theoretical; D015203:Reproducibility of Results
keywords: AHP; Dempster-Shafer evidence theory; dependence; human error probability; human reliability analysis