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Univariate Modeling and Forecasting of Monthly Energy Demand Time Series
 

Summary: Univariate Modeling and Forecasting
of Monthly Energy Demand Time Series
Using Abductive and Neural Networks
R. E. Abdel-Aal
Computer Engineering Department, King Fahd University of Petroleum and Minerals,
Dhahran, Saudi Arabia
Address for corresponding author:
Dr. R. E. Abdel-Aal
P. O. Box 1759
KFUPM
Dhahran 31261
Saudi Arabia
e-mail: radwan@kfupm.edu.sa
Phone: +966 3 860 4320
Fax: +966 3 860 3059
Abstract
Neural networks have been widely used for short-term, and to a lesser degree medium and long term,
demand forecasting. In the majority of cases for the latter two applications, multivariate modeling was
adopted, where the demand time series is related to other weather, socio-economic and demographic time
series. Disadvantages of this approach include the fact that influential exogenous factors are difficult to

  

Source: Abdel-Aal, Radwan E. - Computer Engineering Department, King Fahd University of Petroleum and Minerals

 

Collections: Computer Technologies and Information Sciences; Power Transmission, Distribution and Plants