Vis enkel innførsel

dc.contributor.authorKonila Sriram, Lalitha Madhavi
dc.contributor.authorUlak, Mehmet Baran
dc.contributor.authorOzguven, Eren Erman
dc.contributor.authorArghandeh, Reza
dc.date.accessioned2019-06-03T13:06:47Z
dc.date.available2019-06-03T13:06:47Z
dc.date.created2019-03-31T19:58:24Z
dc.date.issued2019
dc.identifier.citationKonila Sriram, L. M., Ulak, M. B., Ozguven, E. E. & Arghandeh, R. (2019). Multi-network vulnerability causal model for infrastructure co-resilience. IEEE Access, 7, 35344-35358.nb_NO
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/11250/2599750
dc.description.abstractResilience is mostly considered as a single-dimension attribute of a system. Most of the recent works on resilience treat it as a single-dimension attribute of a system or study the different dimensions of the resilience separately without considering its multi-domain nature. In this paper, we propose an advanced causal inference approach combined with machine learning to characterize the spatio-temporal and multi-domain vulnerability of an urban infrastructure system against extreme weather events. With the proposed causality approach, we perform vulnerability assessment for electricity outages and roadway closures through considering the meteorological, topographic, and demographic attributes of urban areas in the aftermath of the extreme weather events. This proposed holistic approach to multi-network vulnerability assessment paves the ground for characterizing the resilience in a multi-network scheme, which is coined as the concept of “co-resilience.” The proposed causal framework for multi-network vulnerability assessment is validated using the actual data for the impacts of the Hurricane Hermine 2016 and the January Storm 2017 on the Tallahassee, FL, USA. The results achieved from the proposed causality approach indicate a high causal relationship among electricity outages, roadway closures, topographic aspects, and meteorological variables in an urban area. Findings show that the proposed multi-network approach for vulnerability assessment improves the performance of the estimation and prediction of the disaster outcomes and the evaluation of the overall system resilience.nb_NO
dc.language.isoengnb_NO
dc.publisherIEEEnb_NO
dc.subjectcausalitynb_NO
dc.subjectresilience vs. co-resiliencenb_NO
dc.subjectmulti-network vulnerabilitynb_NO
dc.subjectextreme eventsnb_NO
dc.subjectpower outagesnb_NO
dc.subjectroadway closuresnb_NO
dc.titleMulti-Network Vulnerability Causal Model for Infrastructure Co-Resiliencenb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.rights.holder© 2019 IEEE.nb_NO
dc.subject.nsiVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420::Sikkerhet og sårbarhet: 424nb_NO
dc.source.pagenumber35344-35358nb_NO
dc.source.volume7nb_NO
dc.source.journalIEEE Accessnb_NO
dc.identifier.doi10.1109/ACCESS.2019.2904457
dc.identifier.cristin1689274
cristin.unitcode203,12,4,0
cristin.unitnameInstitutt for data- og realfag
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel