New method for wind potential prediction using recurrent artificial neural networks

The aim of the study is to find the right architecture of the NARX neural network, in order to perform the daily prediction of the maximum wind speed of Laayoune city. We relied on the Levenberg-Marquardt optimization algorithm. The RMSE error metric showed that NARX-SP outperforms NARX-P.

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Autores principales:	Amellas Yousra, Serag Saif, Loukdache Fahd, Djebli Abdelouahed, Echchelh Adil
Formato:	article
Lenguaje:	EN FR
Publicado:	EDP Sciences 2021
Materias:	Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/0c028d49d3ea44b7a0234a1fa7859d88
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spelling	oai:doaj.org-article:0c028d49d3ea44b7a0234a1fa7859d882021-11-12T11:44:08ZNew method for wind potential prediction using recurrent artificial neural networks2267-124210.1051/e3sconf/202131901111https://doaj.org/article/0c028d49d3ea44b7a0234a1fa7859d882021-01-01T00:00:00Zhttps://www.e3s-conferences.org/articles/e3sconf/pdf/2021/95/e3sconf_vigisan_01111.pdfhttps://doaj.org/toc/2267-1242The aim of the study is to find the right architecture of the NARX neural network, in order to perform the daily prediction of the maximum wind speed of Laayoune city. We relied on the Levenberg-Marquardt optimization algorithm. The RMSE error metric showed that NARX-SP outperforms NARX-P.Amellas YousraSerag SaifLoukdache FahdDjebli AbdelouahedEchchelh AdilEDP SciencesarticleEnvironmental sciencesGE1-350ENFRE3S Web of Conferences, Vol 319, p 01111 (2021)
institution	DOAJ
collection	DOAJ
language	EN FR
topic	Environmental sciences GE1-350
spellingShingle	Environmental sciences GE1-350 Amellas Yousra Serag Saif Loukdache Fahd Djebli Abdelouahed Echchelh Adil New method for wind potential prediction using recurrent artificial neural networks
description	The aim of the study is to find the right architecture of the NARX neural network, in order to perform the daily prediction of the maximum wind speed of Laayoune city. We relied on the Levenberg-Marquardt optimization algorithm. The RMSE error metric showed that NARX-SP outperforms NARX-P.
format	article
author	Amellas Yousra Serag Saif Loukdache Fahd Djebli Abdelouahed Echchelh Adil
author_facet	Amellas Yousra Serag Saif Loukdache Fahd Djebli Abdelouahed Echchelh Adil
author_sort	Amellas Yousra
title	New method for wind potential prediction using recurrent artificial neural networks
title_short	New method for wind potential prediction using recurrent artificial neural networks
title_full	New method for wind potential prediction using recurrent artificial neural networks
title_fullStr	New method for wind potential prediction using recurrent artificial neural networks
title_full_unstemmed	New method for wind potential prediction using recurrent artificial neural networks
title_sort	new method for wind potential prediction using recurrent artificial neural networks
publisher	EDP Sciences
publishDate	2021
url	https://doaj.org/article/0c028d49d3ea44b7a0234a1fa7859d88
work_keys_str_mv	AT amellasyousra newmethodforwindpotentialpredictionusingrecurrentartificialneuralnetworks AT seragsaif newmethodforwindpotentialpredictionusingrecurrentartificialneuralnetworks AT loukdachefahd newmethodforwindpotentialpredictionusingrecurrentartificialneuralnetworks AT djebliabdelouahed newmethodforwindpotentialpredictionusingrecurrentartificialneuralnetworks AT echchelhadil newmethodforwindpotentialpredictionusingrecurrentartificialneuralnetworks
_version_	1718430598456934400

New method for wind potential prediction using recurrent artificial neural networks

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