Abstract
This work provides a preliminary study on applying state-of-the-art time-series forecasting methods to electrical energy consumption data recorded by smart metering equipment. We compare a custom-build commercial baseline method to modern ensemble-based methods from statistical time-series analysis and to a modern commercial GP system. Our preliminary results indicate that that modern ensemble-based methods, as well as GP, are an attractive alternative to custom-built approaches for electrical energy consumption forecasting.
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Flasch, O. et al. (2013). Comparing Ensemble-Based Forecasting Methods for Smart-Metering Data. In: Esparcia-Alcázar, A.I. (eds) Applications of Evolutionary Computation. EvoApplications 2013. Lecture Notes in Computer Science, vol 7835. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37192-9_18
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DOI: https://doi.org/10.1007/978-3-642-37192-9_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37191-2
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