Predicting energy Ccnsumption using artificial neural networks: a case study of the UAE

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Eletter, Shorouq F.;El Refae, Ghaleb A.;Belarbic, Abdelhafid K.;Abu-Rashid, Jamal

Description

Predicting energy consumption is very important for improving resource planning and for more efficient production. This study uses artificial neural network (ANN) models to predict energy consumption in the United Arab Emirates (UAE). The multilayer perceptron model (MLP) and Radial Basis Function (RBF) were used for this purpose. Historical input and output data related to the long-term energy consumption in the UAE were used for training, validation, and testing. The developed neural network models were compared to find the most suitable model with high accuracy.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.4

FAIR Score

50%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

University of Salento

Assigned Domain

Subfield

Electrical and Electronic Engineering

Field

Engineering

Domain

Physical Sciences

Confidence Score

91%

Source

Open Alex

Normalization Factors

FT

44.23

CTw

1.00

MTw

1.00