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dc.contributor.authorBienvenido-Huertas, David
dc.contributor.authorTejedor Herrán, Blanca
dc.contributor.authorCarretero Ayuso, Manuel J.
dc.contributor.authorRodríguez Jiménez, Carlos E
dc.contributor.authorTorres Gonzalez, Marta
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Projectes i de la Construcció
dc.date.accessioned2022-05-26T17:39:56Z
dc.date.issued2022-05-16
dc.identifier.citationBienvenido-Huertas, D. [et al.]. Integrating Artificial Intelligence Approaches for Quantitative and Qualitative Analysis in H-BIM. A: "New Technologies in Building and Construction: Towards Sustainable Development". Berlín: Springer, 2022, p. 243-261.
dc.identifier.isbn978-981-19-1894-0
dc.identifier.urihttp://hdl.handle.net/2117/367761
dc.description.abstractManaging historic buildings is a process in which workers responsible for this task require many time resources. Its optimization through several techniques, such as artificial intelligence, reduces the time related to decision-making. This chapter develops a procedure to generate intelligent GDL objects to predict or estimate the responses required to manage heritage elements in historic buildings. For this purpose, the models developed through data mining procedures in GDL objects in Building Information Modelling (BIM) platforms are combined with their application to historic buildings: Heritage Building Information Modelling (H-BIM). Thus, intelligent BIM models are developed to meet the needs of the technicians responsible for maintaining historic buildings. The responses given by the intelligent objects could be qualitative or quantitative. This methodology would be useful to reduce both the time of decision-making and the data analysis by visualizing them in a three-dimensional model of the historic building. Thus, this is a technique designed to optimize the management of the heritage elements in historic buildings.
dc.format.extent19 p.
dc.language.isoeng
dc.publisherSpringer
dc.subjectÀrees temàtiques de la UPC::Edificació
dc.subject.lcshHistoric buildings -- Conservation and restauration
dc.subject.lcshArtificial intelligence
dc.subject.lcshDecision-making
dc.subject.otherH-BIM
dc.subject.otherArtificial intelligence
dc.subject.otherGDL
dc.titleIntegrating Artificial Intelligence Approaches for Quantitative and Qualitative Analysis in H-BIM
dc.typePart of book or chapter of book
dc.subject.lemacEdificis històrics -- Conservació i restauració
dc.subject.lemacIntel·ligència artificial
dc.subject.lemacDecisió, Presa de
dc.contributor.groupUniversitat Politècnica de Catalunya. GRIC - Grup de Recerca i Innovació de la Construcció
dc.identifier.doi10.1007/978-981-19-1894-0_14
dc.relation.publisherversionhttps://link.springer.com/book/10.1007/978-981-19-1894-0
dc.rights.accessRestricted access - publisher's policy
local.identifier.drac33510823
dc.description.versionPostprint (author's final draft)
dc.date.lift10000-01-01
local.citation.authorBienvenido-Huertas, D; Tejedor, B.; Carretero, M.; Rodríguez, C.; Torres, M.
local.citation.pubplaceBerlín
local.citation.publicationNameNew Technologies in Building and Construction: Towards Sustainable Development
local.citation.startingPage243
local.citation.endingPage261


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