| Publisher DOI: | 10.1109/SEST61601.2024.10694018 | Title: | SMARDcast : day-ahead forecasting of German electricity consumption with deep learning | Language: | English | Authors: | Krüger, Nick Eger, Kolja Renz, Wolfgang |
Other : | Institute of Electrical and Electronics Engineers | Keywords: | CNN-LSTM; neural networks; seasonality; SMARD; time-series forecasting | Issue Date: | 4-Oct-2024 | Publisher: | IEEE | Part of Series: | 2024 International Conference on Smart Energy Systems and Technologies (SEST) | Conference: | International Conference on Smart Energy Systems and Technologies 2024 | URI: | https://hdl.handle.net/20.500.12738/16735 | ISBN: | 979-8-3503-8649-3 979-8-3503-8650-9 |
ISSN: | 2836-4678 | Review status: | This version was peer reviewed (peer review) | Institute: | Department Informations- und Elektrotechnik Fakultät Technik und Informatik |
Type: | Chapter/Article (Proceedings) |
| Appears in Collections: | Publications without full text |
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