Prediction of the daily global solar Irradiation of the great Maghreb region using the complex-valued neural networks

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Lyes Saad Saoud
Fayçal Rahmoune
Victor Tourtchine
Kamel Baddari

Abstract

In this paper, the prediction of the daily global solar irradiation of the great Maghreb’s region using the complex-valued neural networks (CVNN) is presented. This paper is an extension of our recent published work which is the complex-valued forecasting of the global solar irradiation. Both multi-input single-output (MISO) and multi-input multi-output (MIMO) strategies are considered. The data of the capitals of the great Maghreb, which are Tripoli (Libya), Tunis (Tunisia), Algiers (Algeria), Rabat (Morocco), El Aaiun (Western Sahara) and Nouakchott (Mauritania), are used like sample from each country. To test the applicability and the feasibility of the CVNN to predict the daily global irradiation for the great Maghreb case, several models are presented. Results obtained throughout this paper show that the CVNN technique is suitable for prediction of the daily solar irradiation of the region of region of the great Maghreb.

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How to Cite
[1]
L. . Saad Saoud, F. . Rahmoune, V. . Tourtchine, and K. . Baddari, “Prediction of the daily global solar Irradiation of the great Maghreb region using the complex-valued neural networks”, J. Ren. Energies, vol. 17, no. 1, pp. 173 -, Mar. 2014.
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