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

Authors

  • Shorouq F. Eletter Al Ain university
  • Ghaleb A. El Refae Al Ain university
  • Abdelhafid K. Belarbic Al Ain university
  • Jamal Abu-Rashid Al Ain university

DOI:

https://doi.org/10.1285/i20705948v11n1p137

Keywords:

Energy, artificial neural networks, multilayer perceptron model, radial basis function, United Arab Emirates.

Abstract

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.

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Published

27-04-2018