Isbn: 9786206164500 - machine learning based power utilization prediction (4 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Mai 2023, 2023

    6206164500 / 9786206164500

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Condición: Nuevo

    EUR 43,90

    Envío por EUR 23,00 
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    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book summarizes the electricity load forecasting has gained substantial importance nowadays in the modern electrical power management systems with elements of smart greed technology. Power big data has the characteristics of a large number, high dimension and time series. At the same time, there are many forms of missing electric power data, some are missing dispersedly, and some are missing in succession. Therefore, combinations of prediction methods are receiving increasing attention. We performed exploratory data analysis, pre-processing, and train- test split before training the model. We used various metrics to test the advantages of the proposed model: mean absolute error, mean squared error, and root mean squared error. 64 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2023

    6206164500 / 9786206164500

    • Tapa blanda
    • Impresión bajo demanda

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 46,83

    Envío por EUR 35,00 
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    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book summarizes the electricity load forecasting has gained substantial importance nowadays in the modern electrical power management systems with elements of smart greed technology. Power big data has the characteristics of a large number, high dimension and time series. At the same time, there are many forms of missing electric power data, some are missing dispersedly, and some are missing in succession. Therefore, combinations of prediction methods are receiving increasing attention. We performed exploratory data analysis, pre-processing, and train- test split before training the model. We used various metrics to test the advantages of the proposed model: mean absolute error, mean squared error, and root mean squared error.…

  • Idioma: Inglés

    Editorial: LAP Lambert Academic Publishing, 2023

    6206164500 / 9786206164500

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: Nuevo

    EUR 37,23

    Envío por EUR 48,99 
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    Cantidad disponible: Más de 20 disponibles

    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book summarizes the electricity load forecasting has gained substantial importance nowadays in the modern electrical power management systems with elements of smart greed technology. Power big data has the characteristics of a large number, high dimens. …

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Mai 2023, 2023

    6206164500 / 9786206164500

    • Tapa blanda
    • Impresión bajo demanda

    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 43,90

    Envío por EUR 60,00 
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    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book summarizes the electricity load forecasting has gained substantial importance nowadays in the modern electrical power management systems with elements of smart greed technology. Power big data has the characteristics of a large number, high dimension and time series. At the same time, there are many forms of missing electric power data, some are missing dispersedly, and some are missing in succession. Therefore, combinations of prediction methods are receiving increasing attention. We performed exploratory data analysis, pre-processing, and train- test split before training the model. We used various metrics to test the advantages of the proposed model: mean absolute error, mean squared error, and root mean squared error.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.…