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dc.contributor.authorSantos Herrero, José María
dc.contributor.authorLópez Guede, José Manuel ORCID
dc.contributor.authorFlores Abascal, Iván ORCID
dc.contributor.authorZulueta Guerrero, Ekaitz ORCID
dc.date.accessioned2022-08-30T11:53:38Z
dc.date.available2022-08-30T11:53:38Z
dc.date.issued2022
dc.identifier.citationScientific Reports 12 : (2022) // Article ID 8935es_ES
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/10810/57338
dc.description.abstract[EN] Nowadays everyone should be aware of the importance of reducing CO2 emissions which produce the greenhouse effect. In the field of construction, several options are proposed to reach nearly-Zero Energy Building (nZEB) standards. Obviously, before undertaking a modification in any part of a building focused on improving the energy performance, it is generally better to carry out simulations to evaluate its effectiveness. Using Artificial Neural Networks (ANNs) allows a digital twin of the building to be obtained for specific characteristics without using very expensive software. This can simulate the effect of a single or combined intervention on a particular floor or an event on the remaining floors. In this paper, an example has been developed based on ANN. The results show a reasonable correlation between the real data of the Operative Temperature with the Energy Consumption and their estimates obtained through an ANN model, trained using an hourly basis, on each of the floors of an office building. This model confirms it is possible to obtain simulations in existing public buildings with an acceptable degree of precision and without laborious modelling, which would make it easier to achieve the nZEB target, especially in existing public office buildings.es_ES
dc.language.isoenges_ES
dc.publisherNaturees_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectperformancees_ES
dc.subjectefficiencyes_ES
dc.subjectimbalancees_ES
dc.subjectsystemes_ES
dc.subjectheates_ES
dc.titleEnergy and thermal modelling of an office building to develop an artificial neural networks modeles_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creativecommons. org/ licenses/ by/4. 0/es_ES
dc.rights.holderAtribución 3.0 España*
dc.relation.publisherversionhttps://www.nature.com/articles/s41598-022-12924-9es_ES
dc.identifier.doi10.1038/s41598-022-12924-9
dc.departamentoesIngeniería Energéticaes_ES
dc.departamentoesIngeniería de sistemas y automáticaes_ES
dc.departamentoeuEnergia Ingenieritzaes_ES
dc.departamentoeuSistemen ingeniaritza eta automatikaes_ES


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© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International
License, which permits use, sharing, adaptation, distribution and reproduction in any medium or
format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the
Creative Commons licence, and indicate if changes were made. The images or other third party material in this
article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the
material. If material is not included in the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from
the copyright holder. To view a copy of this licence, visit http:// creativecommons. org/ licenses/ by/4. 0/
Except where otherwise noted, this item's license is described as © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creativecommons. org/ licenses/ by/4. 0/