Modeling of Energy Efficiency for Residential Buildings Using Artificial Neuronal Networks
Joint Authors
Rabuñal, J. R.
Álvarez, José Antonio
García-Vidaurrázaga, Dolores
Pazos, Alejandro
Alvarellos-González, Alberto
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-11-28
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Increasing the energy efficiency of buildings is a strategic objective in the European Union, and it is the main reason why numerous studies have been carried out to evaluate and reduce energy consumption in the residential sector.
The process of evaluation and qualification of the energy efficiency in existing buildings should contain an analysis of the thermal behavior of the building envelope.
To determine this thermal behavior and its representative parameters, we usually have to use destructive auscultation techniques in order to determine the composition of the different layers of the envelope.
In this work, we present a nondestructive, fast, and cheap technique based on artificial neural network (ANN) models that predict the energy performance of a house, given some of its characteristics.
The models were created using a dataset of buildings of different typologies and uses, located in the northern area of Spain.
In this dataset, the models are able to predict the U-opaque value of a building with a correlation coefficient of 0.967 with the real U-opaque measured value for the same building.
American Psychological Association (APA)
Álvarez, José Antonio& Rabuñal, J. R.& García-Vidaurrázaga, Dolores& Alvarellos-González, Alberto& Pazos, Alejandro. 2018. Modeling of Energy Efficiency for Residential Buildings Using Artificial Neuronal Networks. Advances in Civil Engineering،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1116601
Modern Language Association (MLA)
Álvarez, José Antonio…[et al.]. Modeling of Energy Efficiency for Residential Buildings Using Artificial Neuronal Networks. Advances in Civil Engineering No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1116601
American Medical Association (AMA)
Álvarez, José Antonio& Rabuñal, J. R.& García-Vidaurrázaga, Dolores& Alvarellos-González, Alberto& Pazos, Alejandro. Modeling of Energy Efficiency for Residential Buildings Using Artificial Neuronal Networks. Advances in Civil Engineering. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1116601
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1116601