Dr.-Ing. Eva Dierkes
Externe wissenschaftliche Mitarbeiterin der AG Optimierung und Optimale SteuerungInformation: Email endet auf @uni-bremen.de
Forschungsgebiete
- Parameteridentifikation in dynamischen Systemen
- Optimierung
- Optimale Steuerung
Projekte
- BESTVILLE (01.04.2024 - 31.03.2025)
- SmartFarm2 (01.02.2021 - 31.08.2024)
- SmartDrive (01.11.2018 - 30.04.2020)
- CAUSE-Cognitive Autonomous Subsurface Exploration (01.04.2015 - 30.09.2018)
Abschlussarbeiten (Auswahl)
- Leistungsprognose von Photovoltaikanlagen: Vergleich rekurrenter neuronaler Netze und Reservoir Computing Modelle (Tim Meyer)
Publikationen (Auswahl)
- E. Dierkes.
On Learning Hamiltonian Systems using Machine Learning with Focus on System Symmetry Preservation.
Dissertationsschrift, Universität Bremen, 2025.DOI: 10.26092/elib/4539
- E. Dierkes, L. Kappertz, V. Solovievskyi, A. Hackenberg, C. Büskens.
Optimized Self-Consumption of Renewable Energies With Forecast-Based Energy Management for Agricultural Farms.
GAMM 94th Annual Meeting of the International Association of Applied Mathematics and Mechanics, 01.12.2024, Magdeburg, Deutschland.
- E. Dierkes, C. Offen, S. Ober-Blöbaum, K. Flaßkamp.
Hamiltonian neural networks with automatic symmetry detection.
Chaos: an Interdisciplinary Journal of Nonlinear Science, 33(6), 2023.DOI: 10.1063/5.0142969
- E. Dierkes, K. Flaßkamp.
Learning Hamiltonian Systems considering System Symmetries in Neural Networks.
The 7th IFAC Workshop on Lagrangian and Hamiltonian Methods for Nonlinear Control, 11.10-13.10.2021, Berlin, Deutschland.
- E. Dierkes, F. Jung, C. Büskens.
Data-based models of drive technology for automation in automotive production.
GAMM 91st Annual Meeting of the international Association of Applied Mathematics and Mechanics, online, 15.03.2021 - 19.03.2021.
Proceedings in Applied Mathematics & Mechanics, 20(1), WILEY-VCH, 2021.