Comparison and Explanation of Forecasting Algorithms for Energy Time Series

In this work, energy time series forecasting competitions from the Schneider Company, the Kaggle Online platform, and the American society ASHRAE were considered. These competitions include power generation and building energy consumption forecasts. The datasets used in these competitions are based...

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Veröffentlicht in:	Mathematics (Basel) Jg. 9; H. 21; S. 2794
Hauptverfasser:	Zhang, Yuyi, Ma, Ruimin, Liu, Jing, Liu, Xiuxiu, Petrosian, Ovanes, Krinkin, Kirill
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.11.2021
Schlagworte:	Accuracy Algorithms Artificial intelligence Competition Datasets Deep learning Energy consumption Energy management ensemble model explainable AI Forecasting Machine learning Mathematical models neural network Neural networks Power consumption Solar energy Time series time series forecasting
ISSN:	2227-7390, 2227-7390
Online-Zugang:	Volltext
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