This book aims to develop a new RSG preversion model based on deep learning. This approach will be able to boost the prediction accuracy of RSG data. Subsequently, the present proposed algorithm effectively handles the dynamics of our targeted weather component by integrating a recurrent and dynamic model named LSTM neural network with an autoregressive process. The raw data available for training this model is divided into two sets, the first is used for the training phase while the second is reserved for testing. The specific objective therefore is to generate accurate semi-hourly RSG forecasts at the level of the city of Er-Rachidia, MOROCCO (Latitude: 31°55′53″N; Longitude: 4°25′35″ W; Elevation: 1039 m), while adopting a powerful learning algorithm named Adam. The indices and results established in this study demonstrate the robustness and confidence that can be adopted to this model which can provide power system managers with reliable forecasts to ensure better management of solar energy and power service systems.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims to develop a new RSG preversion model based on deep learning. This approach will be able to boost the prediction accuracy of RSG data. Subsequently, the present proposed algorithm effectively handles the dynamics of our targeted weather component by integrating a recurrent and dynamic model named LSTM neural network with an autoregressive process. The raw data available for training this model is divided into two sets, the first is used for the training phase while the second is reserved for testing. The specific objective therefore is to generate accurate semi-hourly RSG forecasts at the level of the city of Er-Rachidia, MOROCCO (Latitude: 31°55'53 N; Longitude: 4°25'35 W; Elevation: 1039 m), while adopting a powerful learning algorithm named Adam. The indices and results established in this study demonstrate the robustness and confidence that can be adopted to this model which can provide power system managers with reliable forecasts to ensure better management of solar energy and power service systems. 92 pp. Englisch. N° de réf. du vendeur 9786204333809
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book aims to develop a new RSG preversion model based on deep learning. This approach will be able to boost the prediction accuracy of RSG data. Subsequently, the present proposed algorithm effectively handles the dynamics of our targeted weather compo. N° de réf. du vendeur 536628582
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book aims to develop a new RSG preversion model based on deep learning. This approach will be able to boost the prediction accuracy of RSG data. Subsequently, the present proposed algorithm effectively handles the dynamics of our targeted weather component by integrating a recurrent and dynamic model named LSTM neural network with an autoregressive process. The raw data available for training this model is divided into two sets, the first is used for the training phase while the second is reserved for testing. The specific objective therefore is to generate accurate semi-hourly RSG forecasts at the level of the city of Er-Rachidia, MOROCCO (Latitude: 31°55¿53¿N; Longitude: 4°25¿35¿ W; Elevation: 1039 m), while adopting a powerful learning algorithm named Adam. The indices and results established in this study demonstrate the robustness and confidence that can be adopted to this model which can provide power system managers with reliable forecasts to ensure better management of solar energy and power service systems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 92 pp. Englisch. N° de réf. du vendeur 9786204333809
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book aims to develop a new RSG preversion model based on deep learning. This approach will be able to boost the prediction accuracy of RSG data. Subsequently, the present proposed algorithm effectively handles the dynamics of our targeted weather component by integrating a recurrent and dynamic model named LSTM neural network with an autoregressive process. The raw data available for training this model is divided into two sets, the first is used for the training phase while the second is reserved for testing. The specific objective therefore is to generate accurate semi-hourly RSG forecasts at the level of the city of Er-Rachidia, MOROCCO (Latitude: 31°55'53 N; Longitude: 4°25'35 W; Elevation: 1039 m), while adopting a powerful learning algorithm named Adam. The indices and results established in this study demonstrate the robustness and confidence that can be adopted to this model which can provide power system managers with reliable forecasts to ensure better management of solar energy and power service systems. N° de réf. du vendeur 9786204333809
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Global Solar Radiation Prediction | Using Artificial Neural NetworksCase study: the city of Er-Rachidia, Morocco | Mohamed Khala (u. a.) | Taschenbuch | Englisch | 2021 | Our Knowledge Publishing | EAN 9786204333809 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 120920715
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