Rеvuе des Energies Renouvelables
Volume 19, Numéro 1, Pages 21-28
2016-03-31

A Direct Normal Irradiation Forecasting Model Based On Artificial Neural Networks



Authors : Belhaj I. . El Fatni O. . Barhmi S. . Saidi E.h. .

Abstract

We investigate the forecasting of the hourly Direct Normal Irradiation (DNI) using Artificial Neural Networks (ANN). The data used are hourly satellite data for the region of Ouarzazate in the South West Mediterranean basin region. The database is a total of 19 years. A feed-forward multilayer Perceptron is used with ten input parameters. The results show a very good accuracy for the four seasons of the years forecasted.

Keywords

Forecasting, Artificial neural networks, Direct normal irradiation (DNI), Backpropagation, Perceptron.

Les articles similaires

Intrusion Detection Based On Neural Networks Neural Networks In Iot

Chaima Bensaid . 
pages 29-33.

Forecasting Government Final Consumption Expenditure In Algeria: Comparative Performance Of The Arima (box-jenkins) Model And Artificial Neural Networks (mlp & Lstm) Up To 2034

Lagoune Salim . 
pages 13-27.

Predictive Modeling Of Ozone Dosing In Drinking Water Treatment Plant Using Deep Learning Comparative Study Between Deep Neural Networks And Convolutional Neural Networks

Hellal Aouatef .  Djeddou Messaoud .  Loukam Imed .  A. Hameed Ibrahim .  Al Dallal Jehad .  Shawaqfah Moayyad . 
pages 69-83.

Direct Power Control Based Artificial Neural Networks Of Doubly Fed Induction Generator For Wind Energy Conversion System Application

Djeriri Youcef . 
pages 592-603.

Forecasting Exchange Rates Using Artificial Neural Networks

Benlaria Ahmed .  Boubekeur Lahcen . 
pages 804-814.

Formats de citation