Bastian Steinhagen
bsteinhagen@techfak.uni-bielefeld.dehttps://orcid.org/0000-0002-7905-513X
PEVZ-ID
5 Publikationen
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2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2987581Jungh T, Steinhagen B, Hesse M, Schulte K. Comparison of Different Machine Learning Models for Short-Term Load Forecasting at Transformer Level with High Amounts of Photovoltaic Generation. In: 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE). Piscataway, NJ: IEEE; 2023: 1-5.PUB | DOI
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2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2984934Penner K, Wittenfeld F, Steinhagen B, Hesse M, Rückert U. TinyML optimization for activity classification on the resource-constrained body sensor BI-Vital. In: 2023 IEEE 19th International Conference on Body Sensor Networks (BSN). IEEE; 2023: 1-4.PUB | DOI | Download (ext.)
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2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982608Steinhagen B, Jungh T, Hesse M, et al. Evaluation of the Usage of Edge Computing and LoRa for the Control of Electric Vehicle Charging in the Low Voltage Grid. In: 2023 IEEE PES Conference on Innovative Smart Grid Technologies - Middle East (ISGT Middle East). proceedings. Piscataway, NJ: IEEE; 2023: 1-5.PUB | DOI
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2020 | Datenpublikation | PUB-ID: 2943719Lian Sang C, Steinhagen B, Homburg JD, Adams M, Hesse M, Rückert U. Supplementary Research Data for the Paper entitled Identification of NLOS and Multi-path Conditions in UWB Localization using Machine Learning Methods. Bielefeld University; 2020.PUB | Dateien verfügbar | DOI
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2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2943046Lian Sang C, Steinhagen B, Homburg JD, Adams M, Hesse M, Rückert U. Identification of NLOS and Multi-path Conditions in UWB Localization using Machine Learning Methods. Applied Sciences. 2020;10(11): 3980.PUB | PDF | DOI | Download (ext.) | WoS | Preprint