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2020 – today
- 2023
[c3]Xinyang Wu
, Mohamed El-Shamouty, Christof Nitsche, Marco F. Huber:
Uncertainty-Guided Active Reinforcement Learning with Bayesian Neural Networks. ICRA 2023: 5751-5757- [c2]Xinyang Wu, Elisabeth Wedernikow, Christof Nitsche, Marco F. Huber:
Towards Optimal Energy Management Strategy for Hybrid Electric Vehicle with Reinforcement Learning. IV 2023: 1-7 - [i1]Xinyang Wu, Elisabeth Wedernikow, Christof Nitsche, Marco F. Huber:
Towards Optimal Energy Management Strategy for Hybrid Electric Vehicle with Reinforcement Learning. CoRR abs/2305.12365 (2023)
2010 – 2019
- 2016
- [j2]Philipp Bergmeir, Christof Nitsche, Jurgen Nonnast, Michael Bargende:
Classifying component failures of a hybrid electric vehicle fleet based on load spectrum data - Balanced random forest approaches employing uni- and multivariate decision trees. Neural Comput. Appl. 27(8): 2289-2304 (2016) - 2014
- [c1]Philipp Bergmeir, Christof Nitsche, Jurgen Nonnast, Michael Bargende, Peter Antony, Uwe Keller:
Using Balanced Random Forests on Load Spectrum Data for Classifying Component Failures of a Hybrid Electric Vehicle Fleet. ICMLA 2014: 397-404
2000 – 2009
- 2009
- [j1]Frieder Herb, Achim Frank, Christof Nitsche, Andreas Jossen:
Optimierung der Regelung zwischen Brennstoffzelle und Batterie in Bezug auf Komponentenalterung (Optimization of Fuel Cell and Battery Control in Relation to Component Aging of Fuel Cell Power Train). Autom. 57(1): 40-48 (2009)
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