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Machine Learning Approaches for Energy Forecasting

URN to cite this document:
urn:nbn:de:bvb:355-epub-464471
DOI to cite this document:
10.5283/epub.46447
Lang, Christian
Date of publication of this fulltext: 26 Aug 2021 09:07


Abstract (English)

This thesis focuses on the computation of time series predictions of electricity load series and applies different machine learning methods to the task. In this context, established models were tested and a novel forecasting model utilising convolutional neural networks (CNNs) was developed. The progressing digitisation of the energy market increases the availability of consumption data. At the ...

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Translation of the abstract (German)

Der Fokus der Dissertation liegt auf der Erstellung von Zeitreihenvorhersagen von Stromverbräuchen mittels verschiedener Machine Learning Methoden. Im Rahmen dessen wurden etablierte Modelle getestet und ein neuartiges Vorhersage-Modell entwickelt, welches auf Convolutional Neural Networks (CNN) basiert. Durch die fortschreitende Digitalisierung des Energiemarktes steigt die Verfügbarkeit von ...

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