Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/77895

Registo completo
Campo DCValorIdioma
dc.contributor.authorUrbina, Oscar J.por
dc.contributor.authorTeixeira, Elisabete Rodriguespor
dc.contributor.authorMatos, José M.por
dc.date.accessioned2022-05-25T09:45:14Z-
dc.date.issued2021-05-12-
dc.identifier.isbn9783030736156por
dc.identifier.issn2366-2557por
dc.identifier.urihttps://hdl.handle.net/1822/77895-
dc.description.abstractThe resilience of an area/region/country or society is directly related to the performance of its Critical infrastructures (CI), especially when it is affected by extreme events. The increasing number of catastrophic events, such as terrorist attacks or natural disasters (tsunamis, fires, floods), alerted Europe and other nations worldwide to take measures for preventing or reducing possible consequences against these situations. CI are commonly defined as facilities, systems and assets, essential for the maintenance of vital social functions, and their disruption or destruction may significantly impact the well-being of society. It is mandatory for any nation to identify which Infrastructures must be defined as critical, by analyzing the impacts provoked by an extreme event and the society’s dependence towards this Infrastructure. For this purpose, European Commission established a procedure for the identification and designation of European CI ensuring to avoid different approaches within the EU. Three cross-cutting criteria where defined: (a) Casualties; (b) Economic-effect; (c) Public effect. This paper aims to introduce different risk management models for CI and the parameters necessary for quantification of these Methodologies. There are several models for risk management, the ones studied and introduced in this paper were applied in different countries and types of CI, these vary from deterministic approaches to probabilistic methods. The critically parameters are related in governmental, economical, security and welfare terms, these parameters are important for two main reasons: (1) to keep updated the critical index and the maps of risks and vulnerability that predictive models may use; (2) Current tools are essentially based on models weighed by qualitative weights, not allowing the complete analysis of one-off eventspor
dc.description.sponsorshipFCT -Fundação para a Ciência e a Tecnologia (POCI-01-0247-FEDER-039555)por
dc.language.isoengpor
dc.publisherSpringer Science+Business Mediapor
dc.rightsrestrictedAccesspor
dc.subjectCritical infrastructurespor
dc.subjectExtreme Eventspor
dc.subjectRisk Management Modelspor
dc.subjectPredictive Modelspor
dc.subjectPublic workspor
dc.subjectDisaster preventionpor
dc.subjectPredictive analyticspor
dc.titleIdentification of risk management models and parameters for critical infrastructurespor
dc.typeconferencePaperpor
dc.peerreviewedyespor
sdum.event.title18th International Probabilistic Workshop, IPW 2020por
oaire.citationStartPage391por
oaire.citationEndPage404por
oaire.citationVolume153 LNCEpor
dc.identifier.doi10.1007/978-3-030-73616-3_29por
dc.date.embargo10000-01-01-
dc.subject.fosEngenharia e Tecnologia::Engenharia Civilpor
sdum.journalLecture Notes in Civil Engineeringpor
sdum.conferencePublication18th International Probabilistic Workshop, IPW 2020por
oaire.versionAMpor
dc.subject.odsCidades e comunidades sustentáveispor
Aparece nas coleções:ISISE - Comunicações a Conferências Internacionais

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
Artigo - Conferência IPW2020.pdf
Acesso restrito!
269,25 kBAdobe PDFVer/Abrir

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID