TUdatalib : Supplementary Material | Continual learning for very short-term load forecasting: A Case Study on parts cleaning

dc.contributor.author	Magin, Jonathan
dc.contributor.author	Zink, Robin
dc.date.accessioned	2025-04-04T13:15:28Z
dc.date.available	2025-04-04T13:15:28Z
dc.date.issued	2024-07
dc.identifier.uri	https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4537
dc.description	Here you can find the supplementary material to the paper "Continual learning for very short-term load forecasting: A Case Study on parts cleaning". Experiments were carried out on an industrial Throughput Parts Cleaning Machine (TPCM) at the ETA factory. The machine is equipped with power measurements (1 Hz) on electrical component level. The Dataset contains 1 min averaged data of sensor and control values. Additional informations are provided as text protocol.	de_DE
dc.language.iso	en	de_DE
dc.rights	Creative Commons Attribution 4.0
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	Load forecasting	de_DE
dc.subject	parts cleaning	de_DE
dc.subject	Machine Learning	de_DE
dc.subject.classification	4.43-04 Künstliche Intelligenz und Maschinelle Lernverfahren	de_DE
dc.subject.ddc	004
dc.title	Supplementary Material \| Continual learning for very short-term load forecasting: A Case Study on parts cleaning	de_DE
dc.type	Dataset	de_DE
dc.type	Text	de_DE
tud.project	Bund/BMBF \| 03SFK3A0-3 \| SynErgie3	de_DE
tud.unit	TUDa

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