Please use this identifier to cite or link to this item: https://hdl.handle.net/11681/40299
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dc.contributor.authorJaradat, Raed M.en_US
dc.contributor.authorBuchanan, Randy K.en_US
dc.contributor.authorHossain, Niamat Ullah Ibneen_US
dc.contributor.authorHosseini, Seyedmohsenen_US
dc.contributor.authorMarufuzzaman, Mohammaden_US
dc.creatorInformation Technology Laboratory (U.S.)en_US
dc.creatorMississippi State University. Department of Industrial and Systems Engineeringen_US
dc.creatorUniversity of Southern Mississippien_US
dc.date.accessioned2021-04-15T14:15:46Zen_US
dc.date.available2021-04-15T14:15:46Zen_US
dc.date.issued2021-04en_US
dc.identifier.govdocERDC/ITL MP-21-2en_US
dc.identifier.urihttps://hdl.handle.net/11681/40299en_US
dc.identifier.urihttp://dx.doi.org/10.21079/11681/40299en_US
dc.descriptionMiscellaneous Paperen_US
dc.description.abstractThis research utilizes Bayesian network to address a range of possible risks to the electrical power system and its interdependent networks (EIN) and offers possible options to mitigate the consequences of a disruption. The interdependent electrical infrastructure system in Washington, D.C. is used as a case study to quantify the resilience using the Bayesian network. Quantification of resilience is further analyzed based on different types of analysis such as forward propagation, backward propagation, sensitivity analysis, and information theory. The general insight drawn from these analyses indicate that reliability, backup power source, and resource restoration are the prime factors contributed towards enhancing the resilience of an interdependent electrical infrastructure system.en_US
dc.description.sponsorshipUnited States. Army. Corps of Engineers.en_US
dc.format.extent27 pages / 5.73 MBen_US
dc.format.mediumPDFen_US
dc.language.isoen_USen_US
dc.publisherEngineer Research and Development Center (U.S.)en_US
dc.relation.ispartofseriesMiscellaneous Paper (Engineer Research and Development Center (U.S.)) ; no. ERDC/ITL MP-21-2en_US
dc.relation.isversionofHossain, Niamat Ullah Ibne, Raed Jaradat, Seyedmohsen Hosseini, Mohammad Marufuzzaman, and Randy K. Buchanan. "A framework for modeling and assessing system resilience using a Bayesian network: A case study of an interdependent electrical infrastructure system." International Journal of Critical Infrastructure Protection 25 (2019): 62-83. https://doi.org/10.1016/j.ijcip.2019.02.002en_US
dc.rightsApproved for Public Release; Distribution is Unlimiteden_US
dc.sourceThis Digital Resource was created in Microsoft Word and Adobe Acrobaten_US
dc.subjectBayesian networken_US
dc.subjectElectrical infrastructure systemen_US
dc.subjectSystem resilienceen_US
dc.subjectResilience capacityen_US
dc.titleA framework for modeling and assessing system resilience using a Bayesian network : a case study of an interdependent electrical infrastructure systemsen_US
dc.typeReporten_US
Appears in Collections:Miscellaneous Paper

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