An artificial neural network‐based condition monitoring method for wind turbines, with application to the monitoring of the gearbox P Bangalore, S Letzgus, D Karlsson, M Patriksson Wind Energy 20 (8), 1421-1438, 2017 | 139 | 2017 |
Toward explainable artificial intelligence for regression models: A methodological perspective S Letzgus, P Wagner, J Lederer, W Samek, KR Müller, G Montavon IEEE Signal Processing Magazine 39 (4), 40-58, 2022 | 84 | 2022 |
A sequential pressure-based algorithm for data-driven leakage identification and model-based localization in water distribution networks I Daniel, J Pesantez, S Letzgus, MA Khaksar Fasaee, F Alghamdi, ... Journal of Water Resources Planning and Management 148 (6), 04022025, 2022 | 28 | 2022 |
Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour models S Letzgus Wind Energy Science Discussions 2020, 1-29, 2020 | 19 | 2020 |
A GIS-Based planning approach for urban power and natural gas distribution grids with different heat pump scenarios JM Kisse, M Braun, S Letzgus, TM Kneiske Energies 13 (16), 4052, 2020 | 14 | 2020 |
Marktdesign, Regulierung und Gesamteffizienz von Flexibilität im Stromsystem–Bestandsaufnahme und Herausforderungen H Kondziella, S Graupner, T Bruckner, H Doderer, S Schäfer-Stradowsky, ... Accessed: Dec 11, 2020, 2019 | 9 | 2019 |
Enabling co-innovation for a successful digital transformation in wind energy using a new digital ecosystem and a fault detection case study S Barber, LAM Lima, Y Sakagami, J Quick, E Latiffianti, Y Liu, R Ferrari, ... Energies 15 (15), 5638, 2022 | 5* | 2022 |
A high-resolution pressure-driven method for leakage identification and localization in water distribution networks. Zenodo I Daniel, J Pesantez, S Letzgus, MA Khaksar Fasaee, F Alghamdi, ... | 5 | 2020 |
SCADA-data analysis for condition monitoring of wind turbines S Letzgus | 5 | 2015 |
A high-resolution pressure-driven method for leakage identification and localization in water distribution networks I Daniel, J Pesantez, S Letzgus, MAK Fasaee, F Alghamdi, ... Zenodo, 2020 | 4 | 2020 |
Marktdesign, Regulierung und Gesamteffizienz von Flexibilität im Stromsystem–Bestandsaufnahme und Herausforderungen [WindNODEArbeitspaket 5 „Marktdesign und Regulierung–neue … H Kondziella, S Graupner, T Bruckner, H Doderer, S Schäfer-Stradowsky, ... | 4 | 2019 |
An explainable AI framework for robust and transparent data-driven wind turbine power curve models S Letzgus, KR Müller Energy and AI 15, 100328, 2024 | 3 | 2024 |
Towards transparent ANN wind turbine power curve models. S Letzgus arXiv preprint arXiv:2210.12104, 2022 | 1 | 2022 |
XpertAI: uncovering model strategies for sub-manifolds S Letzgus, KR Müller, G Montavon arXiv preprint arXiv:2403.07486, 2024 | | 2024 |
Towards transparent and robust data-driven wind turbine power curve models S Letzgus, KR Müller arXiv preprint arXiv:2304.09835, 2023 | | 2023 |
XAI for transparent wind turbine power curve models S Letzgus arXiv preprint arXiv:2210.12104, 2022 | | 2022 |
Training data requirements for SCADA based condition monitoring using artificial neural networks S Letzgus 15th EAWE PhD Seminar on Wind Energy, 2019 | | 2019 |
SCADA-based anomaly detection – challenges for automated application of artificial neural networks S Letzgus 14th EAWE PhD Seminar on Wind Energy, 2018 | | 2018 |
Integrated Intelligence Assessment For Energy Systems S Letzgus, C Koch, G Erdmann Transforming Energy Markets, 41st IAEE International Conference, Jun 10-13, 2018, 2018 | | 2018 |
Energy and AI S Letzgus, KR Müller | | |