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dc.contributor.authorGonzález Cardenas, Rubén
dc.contributor.authorNebot Castells, M. Àngela
dc.contributor.authorMúgica Álvarez, Francisco
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2020-09-10T10:14:25Z
dc.date.available2020-09-10T10:14:25Z
dc.date.issued2020-04-26
dc.identifier.citationCárdenas, R.; Nebot, A.; Múgica, F. Integral seismic risk assessment through fuzzy models. "Applied sciences", 26 Abril 2020, vol. 10, núm. 9, art. 3017, p. 1-20.
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/2117/328640
dc.description.abstractThe usage of indicators as constituent parts of composite indices is an extended practice in many fields of knowledge. Even if rigorous statistical analyses are implemented, many of the methodologies follow simple arithmetic assumptions to aggregate indicators to build an index. One of the consequences of such assumptions can be the concealment of the influence of some of the composite index’s components. We developed a fuzzy method that aggregates indicators using non-linear methods and, in this paper, compare it to a well-known example in the field of risk assessment, called Moncho’s equation, which combines physical and social components and uses a linear aggregation method to estimate a level of seismic risk. By comparing the spatial pattern of the risk level obtained from these two methodologies, we were able to evaluate to what extent a fuzzy approach allows a more realistic representation of how social vulnerability levels might shape the seismic risk panorama in an urban environment. We found that, in some cases, this approach can lead to risk level values that are up to 80% greater than those obtained using a linear aggregation method for the same areas.
dc.format.extent20 p.
dc.language.isoeng
dc.publisherMultidisciplinary Digital Publishing Institute
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed.en
dc.subjectÀrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject.lcshFuzzy systems
dc.subject.lcshRisk assessment
dc.subject.lcshSeismology
dc.subject.otherComposite indices
dc.subject.otherFuzzy models
dc.subject.otherIndicator aggregation
dc.subject.otherSeismic vulnerability
dc.subject.otherSocial vulnerability
dc.subject.otherDisaster risk reduction
dc.titleIntegral seismic risk assessment through fuzzy models
dc.typeArticle
dc.subject.lemacSistemes borrosos
dc.subject.lemacAvaluació del risc
dc.subject.lemacSismologia
dc.contributor.groupUniversitat Politècnica de Catalunya. SOCO - Soft Computing
dc.identifier.doi10.3390/app10093017
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.mdpi.com/2076-3417/10/9/3017
dc.rights.accessOpen Access
local.identifier.drac28997146
dc.description.versionPostprint (published version)
local.citation.authorCárdenas, R.; Nebot, A.; Múgica, F.
local.citation.publicationNameApplied sciences
local.citation.volume10
local.citation.number9, art. 3017
local.citation.startingPage1
local.citation.endingPage20


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Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution 4.0 Generic