Prédiction De La Vitesse Du Vent A Différents Horizons De Prévision A L'aide Des Réseaux De Neurones Artificiels

dc.contributor.authorTadjine Aymen, Ammari Imane
dc.date.accessioned2022-10-02T10:52:50Z
dc.date.available2022-10-02T10:52:50Z
dc.date.issued2022-10-02
dc.description.abstractThere are many renewable energy sourcesAvailable, including wind energy, this energy is associated with changes in wind speed that constantly change over time. This makes the amount of wind power produced uncertain. Therefore, predicting wind speed will help estimate before wind power generation for the electricity grid is available. In order to make good use of this energy, several strategies have been proposed in the literature for the good use of wind energy, including the implementation of wind speed prediction systems and physical methods.... etc. In this context, this study focuses on predicting future wind speeds in different time scales of data measured in a given location using synthetic neural networks (RNA). As comparative criteria between these models, we choose Error (RMSE), Absolute Medium Bias Error (MABE), Absolute Percentage Error (MAPE) and Determination Factoren_US
dc.identifier.other2022
dc.identifier.urihttps://depot.univ-msila.dz/handle/123456789/32738
dc.language.isofren_US
dc.publisheruniversity of M'silaen_US
dc.subjectartificial intelligence, synthetic neural networks, series Time, Prediction, Wind Speeden_US
dc.titlePrédiction De La Vitesse Du Vent A Différents Horizons De Prévision A L'aide Des Réseaux De Neurones Artificielsen_US
dc.typeThesisen_US

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