Data-Driven Tools for Building Energy Consumption Prediction: A Review

Razak Olu-Ajayi; Hafiz Alaka; Hakeem Owolabi; Lukman Akanbi; Sikiru Ganiyu

doi:10.3390/en16062574

Data-Driven Tools for Building Energy Consumption Prediction: A Review

Razak Olu-Ajayi^*, Hafiz Alaka, Hakeem Owolabi, Lukman Akanbi, Sikiru Ganiyu

^*Corresponding author for this work

Research output: Contribution to journal › Review article › peer-review

31 Citations (SciVal)

Original language	English
Article number	2574
Journal	Energies
Volume	16
Issue number	6
DOIs	https://doi.org/10.3390/en16062574
Publication status	Published (VoR) - Mar 2023

Keywords

building energy consumption prediction
data driven tools
energy conservation
energy efficiency
energy prediction
machine learning

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10.3390/en16062574

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title = "Data-Driven Tools for Building Energy Consumption Prediction: A Review",

keywords = "building energy consumption prediction, data driven tools, energy conservation, energy efficiency, energy prediction, machine learning",

author = "Razak Olu-Ajayi and Hafiz Alaka and Hakeem Owolabi and Lukman Akanbi and Sikiru Ganiyu",

note = "Publisher Copyright: {\textcopyright} 2023 by the authors.",

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volume = "16",

journal = "Energies",

issn = "1996-1073",

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T2 - A Review

AU - Olu-Ajayi, Razak

AU - Alaka, Hafiz

AU - Owolabi, Hakeem

AU - Akanbi, Lukman

AU - Ganiyu, Sikiru

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KW - building energy consumption prediction

KW - data driven tools

KW - energy conservation

KW - energy efficiency

KW - energy prediction

KW - machine learning

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U2 - 10.3390/en16062574

DO - 10.3390/en16062574

M3 - Review article

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VL - 16

JO - Energies

JF - Energies

IS - 6

M1 - 2574

ER -

Data-Driven Tools for Building Energy Consumption Prediction: A Review

Keywords

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