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A Hierarchal Risk Assessment Model using the Evidential Reasoning Rule
Version 1
: Received: 4 November 2016 / Approved: 9 November 2016 / Online: 9 November 2016 (10:29:29 CET)
A peer-reviewed article of this Preprint also exists.
Ji, X.; Jiang, J.; Sun, J.; Chen, Y.-W. A Hierarchal Risk Assessment Model Using the Evidential Reasoning Rule. Systems 2017, 5, 9. Ji, X.; Jiang, J.; Sun, J.; Chen, Y.-W. A Hierarchal Risk Assessment Model Using the Evidential Reasoning Rule. Systems 2017, 5, 9.
Abstract
This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER) rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1) formulation of risk assessment hierarchy, (2) representation of both qualitative and quantitative information, (3) elicitation of attribute weights and information reliabilities, (4) aggregation of assessment information using the ER rule and (5) quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.
Keywords
Risk assessment; Evidential reasoning; Fire/explosion
Subject
MATHEMATICS & COMPUTER SCIENCE, Information Technology & Data Management
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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