A hybrid neuro-fuzzy inference system-based algorithm for time series forecasting applied to energy consumption prediction

•A neuro-fuzzy inference system boosted with a recent optimizer is proposed.•A new layer denominated as non-working time adaptation was proposed.•Autoregressive process is applied to generate significant endogenous inputs.•Hourly energy consumption of a Faculty building is accurately predicted. The...

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Vydáno v:	Applied energy Ročník 268; s. 114977
Hlavní autoři:	Jallal, Mohammed Ali, González-Vidal, Aurora, Skarmeta, Antonio F., Chabaa, Samira, Zeroual, Abdelouhab
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 15.06.2020
Témata:	algorithms ANFIS Autoregressive process Building energy consumption buildings California data collection energy fuzzy logic gender differences Gender-difference firefly algorithm prediction Spain time series analysis Time series forecasting California Spain Time series forecasting Gender-difference firefly algorithm Autoregressive process ANFIS Building energy consumption
ISSN:	0306-2619, 1872-9118
On-line přístup:	Získat plný text
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