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Methodological Framework of Artificial Intelligence Algorithms and Generation of the Dataset

dc.contributor.authorBienvenido Huertas, David
dc.contributor.authorRubio Bellido, Carlos
dc.date.accessioned2022-11-25T07:02:29Z
dc.date.available2022-11-25T07:02:29Z
dc.date.issued2021
dc.identifier.citationBienvenido-Huertas, D., Rubio-Bellido, C. (2021). Methodological Framework of Artificial Intelligence Algorithms and Generation of the Dataset. In: Optimization of the Characterization of the Thermal Properties of the Building Envelope. SpringerBriefs in Applied Sciences and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-63629-6_3es
dc.identifier.isbn2191530X
dc.identifier.urihttp://hdl.handle.net/20.500.12251/2705
dc.description.abstractThe analysis of the state-of-the-art methods to characterize thermal properties has shown the importance of the theoretical methods (both of stationary and periodic properties) and the difficulty to characterize the existing buildings correctly. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.es
dc.language.isoenges
dc.publisherSpringer Science and Business Media Deutschland GmbHes
dc.titleMethodological Framework of Artificial Intelligence Algorithms and Generation of the Datasetes
dc.typebookPartes
dc.identifier.doi10.1007/978-3-030-63629-6_3
dc.identifier.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85096526743&doi=10.1007%2f978-3-030-63629-6_3&partnerID=40&md5=1180c54adae2be2ff061c5977cd03d4aes
dc.issue.numberes
dc.page.initial31es
dc.page.final45es
dc.subject.keywordEnvolvente de edificioes
dc.subject.keywordPropiedades térmicases
dc.subject.keywordRendimiento energéticoes
dc.subject.keywordNormativa construcciónes
dc.subject.unesco3305.14 Viviendases
dc.subject.unesco3305.90 Transmisión de Calor en la Edificaciónes
dc.subject.unesco3311.02 Ingeniería de Controles
dc.volume.numberes


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