Using decision trees to extract decision rules from police reports on road accidents

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dc.contributor.affiliationDepartamento de Ingeniería e Infraestructura de los Transportes
dc.contributor.affiliationInstituto del Transporte y Territorio
dc.contributor.affiliationEscuela Técnica Superior de Ingeniería de Caminos, Canales y Puertos
dc.contributor.authorLópez-Maldonado, Griselda
dc.contributor.authorDe Oña, J.es_ES
dc.contributor.authorAbellán, J.es_ES
dc.contributor.funderJunta de Andalucíaes_ES
dc.contributor.funderDirección General de Tráfico
dc.date.accessioned2020-10-21T03:31:10Z
dc.date.available2020-10-21T03:31:10Z
dc.date.issued2012-10-03es_ES
dc.description.abstract[EN] The World Health Organization (WHO) considers that traffic accidents are major public health problem worldwide, for this reason safety managers try to identify the main factors affecting the severity as consequence of road accidents. In order to identify these factors, in this paper, Data Mining (DM) techniques such as Decision Trees (DTs), have been used. A dataset of traffic accidents on rural roads in the province of Granada (Spain) have been analyzed. DTs allow certain decision rules to be extracted. These rules could be used in future road safety campaigns and would enable managers to implement certain priority actions. (C) 2012 The Authors. Published by Elsevier Ltd. Selection and/or peer-review under responsibility of SIIV2012 Scientific Committeeen_EN
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationLópez-Maldonado, G.; De Oña, J.; Abellán, J. (2012). Using decision trees to extract decision rules from police reports on road accidents. Procedia - Social and Behavioral Sciences. 53:106-114. https://doi.org/10.1016/j.sbspro.2012.09.864es_ES
dc.description.sponsorshipThe authors are grateful to the Spanish General Directorate of Traffic (DGT) for providing the data necessary for this research. Griselda Lopez wishes to express her acknowledgement to the regional ministry of Economy, Innovation and Science of the regional government of Andalusia (Spain) for their scholarship to train teachers and researchers in Deficit Areas, which has made this work possible.es_ES
dc.description.upvformatpfin114es_ES
dc.description.upvformatpinicio106es_ES
dc.description.volume53es_ES
dc.identifier.doi10.1016/j.sbspro.2012.09.864es_ES
dc.identifier.issn1877-0428es_ES
dc.identifier.urihttps://riunet.upv.es/handle/10251/152714
dc.languageIngléses_ES
dc.publisherElsevieres_ES
dc.relation.conferencedateOctubre 29-31,2012es_ES
dc.relation.conferencename5th International Congress - Sustainability of Road Infrastructureses_ES
dc.relation.conferenceplaceRome, Italyes_ES
dc.relation.ispartofProcedia - Social and Behavioral Scienceses_ES
dc.relation.pasarelaS\399213es_ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.sbspro.2012.09.864es_ES
dc.rightsReconocimiento - No comercial - Sin obra derivada (by-nc-nd)es_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectDriver injury severityes_ES
dc.subjectLogistic-Regressiones_ES
dc.subjectModelses_ES
dc.subject.classificationINGENIERIA E INFRAESTRUCTURA DE LOS TRANSPORTESes_ES
dc.titleUsing decision trees to extract decision rules from police reports on road accidentses_ES
dc.typeArtículoes_ES
dc.typeComunicación en congresoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
person.identifier582490
person.identifier.orcid0000-0001-9012-0599
relation.isAuthorOfPublicatione9d2141b-6a91-43c3-b3e4-786aed81828c
relation.isAuthorOfPublication.latestForDiscoverye9d2141b-6a91-43c3-b3e4-786aed81828c
relation.isOrgUnitOfPublication9e95c1d2-4843-4f36-9f12-84277b110b62
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