Please use this identifier to cite or link to this item:
http://dspace.ucuenca.edu.ec/handle/123456789/37881
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Duque Perez, Oscar | - |
dc.contributor.author | Mariano Hernández, Deyslen | - |
dc.contributor.author | Hernández Callejo, Luis | - |
dc.contributor.author | Solís, Martín | - |
dc.contributor.author | Santos García, Felix | - |
dc.contributor.author | Gonzalez Morales, Luis Gerardo | - |
dc.contributor.author | Zorita Lamadrid, Ángel Luis | - |
dc.date.accessioned | 2022-01-28T14:39:18Z | - |
dc.date.available | 2022-01-28T14:39:18Z | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 2076-3417 | - |
dc.identifier.uri | http://dspace.ucuenca.edu.ec/handle/123456789/37881 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114110387&doi=10.3390%2fapp11177886&partnerID=40&md5=04c6c1521938105f1a7ceab00ba6e9a7 | - |
dc.description.abstract | Smart buildings seek to have a balance between energy consumption and occupant com-fort. To make this possible, smart buildings need to be able to foresee sudden changes in the build-ing’s energy consumption. With the help of forecasting models, building energy management sys-tems, which are a fundamental part of smart buildings, know when sudden changes in the energy consumption pattern could occur. Currently, different forecasting methods use models that allow building energy management systems to forecast energy consumption. Due to this, it is increasingly necessary to have appropriate forecasting models to be able to maintain a balance between energy consumption and occupant comfort. The objective of this paper is to present an energy consumption forecasting strategy that allows hourly day-ahead predictions. The presented forecasting strategy is tested using real data from two buildings located in Valladolid, Spain. Different machine learning and deep learning models were used to analyze which could perform better with the proposed strategy. After establishing the performance of the models, a model was assembled using the mean of the prediction values of the top five models to obtain a model with better performance. © 2021 by the authors. Licensee MDPI, Basel, Switzerland | - |
dc.language.iso | es_ES | - |
dc.source | Applied Sciences | - |
dc.subject | Smart building | - |
dc.subject | Energy consumption | - |
dc.subject | Forecasting models | - |
dc.subject | Multi-step forecasting | - |
dc.subject | Short-term forecasting | - |
dc.title | A data-driven forecasting strategy to predict continuous hourly energy demand in smart buildings | - |
dc.type | ARTÍCULO | - |
dc.ucuenca.idautor | 0000-0003-4750-1198 | - |
dc.ucuenca.idautor | 1729711059 | - |
dc.ucuenca.idautor | 0000-0003-2973-3657 | - |
dc.ucuenca.idautor | 0000-0002-8822-2948 | - |
dc.ucuenca.idautor | 0000-0002-4255-3450 | - |
dc.ucuenca.idautor | 0000-0001-7593-691X | - |
dc.ucuenca.idautor | 0000-0003-2994-2520 | - |
dc.identifier.doi | 10.3390/app11177886 | - |
dc.ucuenca.version | Versión publicada | - |
dc.ucuenca.areaconocimientounescoamplio | 05 - Ciencias Físicas, Ciencias Naturales, Matemáticas y Estadísticas | - |
dc.ucuenca.afiliacion | Solís, M., Instituto Tecnológico de Costa Rica (ITCR), Cartago, Costa rica | - |
dc.ucuenca.afiliacion | Gonzalez, L., Universidad de Cuenca, Departamento de Ingeniería Eléctrica, Electrónica y Telecomunicaciones(DEET), Cuenca, Ecuador | - |
dc.ucuenca.afiliacion | Hernández, L., Universidad de Valladolid, Soria, España | - |
dc.ucuenca.afiliacion | Zorita, Á., Universidad de Valladolid, Soria, España | - |
dc.ucuenca.afiliacion | Mariano, D., Universidad de Valladolid, Soria, España | - |
dc.ucuenca.afiliacion | Santos, F., Instituto Tecnológico de Santo Domingo INTEC, Santo Domingo, Republica dominicana | - |
dc.ucuenca.afiliacion | Duque, O., Universidad de Valladolid, Soria, España | - |
dc.ucuenca.correspondencia | Hernández Callejo, Luis, uis.hernandez.callejo@uva.es | - |
dc.ucuenca.correspondencia | Mariano Hernández, Deyslen, deyslen.mariano@intec.edu.do | - |
dc.ucuenca.volumen | Volumen 11, número 17 | - |
dc.ucuenca.indicebibliografico | SCOPUS | - |
dc.ucuenca.factorimpacto | 0.44 | - |
dc.ucuenca.cuartil | Q2 | - |
dc.ucuenca.numerocitaciones | 0 | - |
dc.ucuenca.areaconocimientofrascatiamplio | 1. Ciencias Naturales y Exactas | - |
dc.ucuenca.areaconocimientofrascatiespecifico | 1.5 Ciencias de la Tierra y el Ambiente | - |
dc.ucuenca.areaconocimientofrascatidetallado | 1.5.8 Ciencias del Medioambiente | - |
dc.ucuenca.areaconocimientounescoespecifico | 053 - Ciencias Físicas | - |
dc.ucuenca.areaconocimientounescodetallado | 0533 - Física | - |
dc.ucuenca.urifuente | https://www.mdpi.com/journal/applsci/special_issues/AI_Smart_Buildings | - |
Appears in Collections: | Artículos |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
documento.pdf | document | 8.37 MB | Adobe PDF | View/Open |
This item is protected by original copyright |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
Centro de Documentacion Regional "Juan Bautista Vázquez" | ||||||||||
|