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dc.contributor.authorBienvenido Huertas, José David 
dc.contributor.authorNieto-Julián, Juan Enrique
dc.contributor.authorMoyano, Juan José
dc.contributor.authorMacías Bernal, Juan Manuel
dc.contributor.authorCastro, José
dc.date.accessioned2024-02-09T11:30:20Z
dc.date.available2024-02-09T11:30:20Z
dc.date.issued2019-03-23
dc.identifier.urihttps://hdl.handle.net/10481/88855
dc.description.abstractThe preservation of the architectural heritage is characterized by the intervention of different technicians, who may disagree on decision-making criteria. In recent years, the H-BIM methodology has emerged to manage these buildings, although the multidisciplinary technical personnel make the decision-taking something of a challenge. In this regard, artificial intelligence may be an opportunity to establish automatic responses, thus optimizing the process. This article proposes a methodology to implement models of classification using the J48 algorithm in a H-BIM model. The case study was focused on a tiles panel from a building which belongs to the Real Alcazar of Seville. First, a model of classification was developed to estimate the degree of intervention with an adequate degree of adjustment. Then, the model was implemented in the H-BIM software by programming using GDL. This methodology automates the decision-making and reduces times of assessments, visualizing and managing the information in the H-BIM model.es_ES
dc.language.isoenges_ES
dc.publisherTaylor & Francises_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectArtificial intelligencees_ES
dc.subjectDecision treeses_ES
dc.subjectGeometric description languagees_ES
dc.subjectJ48 algorithmes_ES
dc.subjectH-BIM projectes_ES
dc.subjectPavilion of Charles Ves_ES
dc.titleImplementing Artificial Intelligence in H-BIM Using the J48 Algorithm to Manage Historic Buildingses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/embargoedAccesses_ES
dc.identifier.doi10.1080/15583058.2019.1589602
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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