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Correlation and dependency in multivariate process risk assessment
conference contribution
posted on 2023-05-23, 12:34 authored by Hashemi, SJ, Ahmed, S, Faisal KhanFaisal KhanProcess safety and risk assessment are often multidimensional and hence require the joint modeling of several potentially correlated random variables. Any effort to address the correlation among the input variables is important and could improve the accuracy in practical applications of risk assessment models. This paper discusses the problems with correlated variables used in risk assessment and presents a copula-based technique to model dependency among variables to improve uncertainty analysis. Using the copula approach, capturing the dependence structure among different risk factors and estimating the univariate risk marginals can be separated. This advantage simplifies the overall risk estimation for systems with multiple dependent risk sources. The advantage of the copula-based framework for generalization over the traditional correlation analysis technique is demonstrated using a case study. Methods are also presented for copula selection and estimation of the copula parameters.
History
Publication title
Proceedings of the 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015Volume
48Editors
D MaquinPagination
1339-1344ISSN
2405-8963Department/School
Australian Maritime CollegePublisher
Elsevier B.V.Place of publication
The NetherlandsEvent title
9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS 2015Event Venue
Paris, FranceDate of Event (Start Date)
2015-09-02Date of Event (End Date)
2015-09-04Rights statement
Copyright 2015 IFACRepository Status
- Restricted