Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/128641
Title: Application of fuzzy and conventional forecasting techniques to predict energy consumption in buildings
Authors: Cabrera Rodriguez, Axel 
B. Ruiz, L. G.
Criado-Ramon, D.
Barranco, C. D.
Pegalajar, M. C.
Editors: Li, Jin
UNESCO Clasification: 120317 Informática
Issue Date: 2023
Journal: International Journal of Intelligent Systems 
Abstract: This paper presents the implementation and analysis of two approaches (fuzzy and conventional). Using hourly data from buildings at the University of Granada, we have examined their electricity demand and designed a model to predict energy consumption. Our proposal was conducted with the aid of time series techniques as well as the combination of artificial neural networks and clustering algorithms. Both approaches proved to be suitable for energy modelling although nonfuzzy models provided more variability and less robustness than fuzzy ones. Despite the relatively small difference between fuzzy and nonfuzzy estimates, the results reported in this study show that the fuzzy solution may be useful to enhance and enrich energy predictions.
URI: http://hdl.handle.net/10553/128641
ISSN: 0884-8173
DOI: 10.1155/2023/4391555
Source: International Journal of Intelligent Systems, vol. 2023, Article ID 4391555 (2023)
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