Übersicht			Auf mobile öffnen

Lieferstatus:	i.d.R. innert 7-14 Tagen versandfertig
Veröffentlichung:	Mai 2022
Genre:	Ratgeber
ISBN:	9783036542188
EAN-Code:	9783036542188
Verlag:	Mdpi Ag
Einband:	Gebunden
Sprache:	English
Dimensionen:	H 250 mm / B 175 mm / D 13 mm
Gewicht:	520 gr
Seiten:	128
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This reprint introduces advanced prediction models focused on power load forecasting. Models based on artificial intelligence and more traditional approaches are shown, demonstrating the real possibilities of use to improve prediction in this field. Models of LSTM neural networks, LSTM networks with a SESDA architecture, in even LSTM-CNN are used. On the other hand, multiple seasonal Holt-Winters models with discrete seasonality and the application of the Prophet method to demand forecasting are presented. These models are applied in different circumstances and show highly positive results. This reprint is intended for both researchers related to energy management and those related to forecasting, especially power load.