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doi:10.24405/14540
| Title: | Automated Anomaly Detection and Diagnosis of the Environmental Control System of the ISS | Authors: | Moddemann, Lukas Steude, Henrik Sebastian Niggemann, Oliver Grashorn, Philipp |
Language: | eng | Keywords: | dtec.bw;Machine learning;Anomaly detection;Cyber-physical systems;Diagnosis | Subject (DDC): | 500 Naturwissenschaften 620 Ingenieurwissenschaften |
Issue Date: | 2022 | Document Type: | Book Part | Project: | Künstliche Intelligenz für die Diagnose der Internationalen Raumstation ISS | Page Start: | 123 | Page End: | 128 | Published in (Book): | dtec.bw-Beiträge der Helmut-Schmidt-Universität / Universität der Bundeswehr Hamburg: Forschungsaktivitäten im Zentrum für Digitalisierungs- und Technologieforschung der Bundeswehr dtec.bw - Band 1 · 2022 | is Part of: | https://doi.org/10.24405/14522 | Organization Units (connected with the publication): | Informatik im Maschinenbau DTEC.bw |
DOI: | https://doi.org/10.24405/14540 | ISBN: | 978-3-86818-315-3 |
| Appears in Collections: | 1 - Open Access Publications (except Theses) |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| openHSU_14540.pdf | 1.66 MB | Adobe PDF | View/Open |
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