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Global Solar Radiation Prediction: Using Artificial Neural NetworksCase study: the city of Er-Rachidia, Morocco - Brossura
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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.
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Global Solar Radiation Prediction
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Our Knowledge Publishing Dez 2021, 2021
ISBN 10: 6204333801
ISBN 13: 9786204333809
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9786204333809
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Global Solar Radiation Prediction
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Condizione: 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. Codice articolo 536628582
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Global Solar Radiation Prediction : Using Artificial Neural NetworksCase study: the city of Er-Rachidia, Morocco
Editore:
Our Knowledge Publishing, 2021
ISBN 10: 6204333801
ISBN 13: 9786204333809
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Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9786204333809
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Global Solar Radiation Prediction
Editore:
Our Knowledge Publishing Dez 2021, 2021
ISBN 10: 6204333801
ISBN 13: 9786204333809
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9786204333809
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Global Solar Radiation Prediction | Using Artificial Neural NetworksCase study: the city of Er-Rachidia, Morocco
Editore:
Our Knowledge Publishing, 2021
ISBN 10: 6204333801
ISBN 13: 9786204333809
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Da: preigu, Osnabrück, Germania
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Taschenbuch. Condizione: 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: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Codice articolo 120920715
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