العربية

Research

  • Research
  • Predicting energy Consumption using artificial neural networks: a cas...
Other

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

May 30, 2018

DOI:

Published in: Electronic Journal of Applied Statistical Analysis

Shorouq F Eletter Ghaleb A El Refae Abdelhafid K Belarbic

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.

Other Researches

Marketing Intelligence in the Era of Big Data

Big data: ethical issues

Exploring interns’ satisfaction: A case study of United Arab Emirates.

Generational Diversity and Work Values

Loan decision models for the Jordanian commercial banks

Big Data: Unleashing The Match Between Quality and Quantity

Credit risk assessment model for Jordanian commercial banks: neural scoring approach

Credit risk management for the Jordanian commercial banks: A business intelligence approach

Using data mining for an intelligent marketing campaign

Neuro-based artificial intelligence model for loan decisions

Applying neural networks for loan decisions in the Jordanian commercial banking system

Islamic entrepreneurship: an ongoing driver for social

Neural networks in bank insolvency prediction

Copyright © 2024 Al Ain University. All Rights Reserved.