| Data-driven prediction of added-wave resistance on ships in oblique waves—A comparison between tree-based ensemble methods and artificial neural networks M Mittendorf, UD Nielsen, HB Bingham Applied Ocean Research 118, 102964, 2022 | 27 | 2022 |
| Sea state identification using machine learning—A comparative study based on in-service data from a container vessel M Mittendorf, UD Nielsen, HB Bingham, G Storhaug Marine Structures 85, 103274, 2022 | 24 | 2022 |
| Hydrodynamic hull form optimization of fast catamarans using surrogate models M Mittendorf, AD Papanikolaou Ship Technology Research 68 (1), 14-26, 2021 | 24 | 2021 |
| Towards the uncertainty quantification of semi-empirical formulas applied to the added resistance of ships in waves of arbitrary heading M Mittendorf, UD Nielsen, HB Bingham, S Liu Ocean Engineering 251, 111040, 2022 | 10 | 2022 |
| Wave spectrum estimation conditioned on machine learning-based output using the wave buoy analogy UD Nielsen, M Mittendorf, Y Shao, G Storhaug Marine Structures 91, 103470, 2023 | 8 | 2023 |
| The prediction of sea state parameters by deep learning techniques using ship motion data M Mittendorf, UD Nielsen, HB Bingham 7th World Maritime Technology Conference 2022, 2022 | 5 | 2022 |
| Capturing the effect of biofouling on ships by incremental machine learning M Mittendorf, UD Nielsen, HB Bingham Applied Ocean Research 138, 103619, 2023 | 2 | 2023 |
| Assessment of added resistance estimates based on monitoring data from a fleet of container vessels M Mittendorf, UD Nielsen, HB Bingham, J Dietz Ocean Engineering 272, 113892, 2023 | 2 | 2023 |
| Towards Improved Prediction of Ship Performance: A Comparative Analysis on In-service Ship Monitoring Data for Modeling the Speed-Power Relation S DeKeyser, C Morobé, M Mittendorf arXiv preprint arXiv:2212.13061, 2022 | 2 | 2022 |
| Estimating waves via measured ship responses UD Nielsen, HB Bingham, AH Brodtkorb, T Iseki, JJ Jensen, M Mittendorf, ... Scientific Reports 13 (1), 17342, 2023 | 1 | 2023 |
| Data-driven Prediction of Added Resistance on Ships in Waves M Mittendorf Technical University of Denmark, 2023 | 1 | 2023 |
| Deep Learning-Based Sea State Estimation Using Sensor Data of Wave-Induced Ship Responses M Mittendorf, UD Nielsen 2nd Marine AI Open Seminar in AY2022 (TUMSAT): Advanced Case Studies of …, 2022 | 1 | 2022 |
| Uncertainty aware Prediction of Added Resistance using an Adapted Semi empirical Formula M Mittendorf, UD Nielsen, HB Bingham, S Liu DNV Nordic Maritime Universities Workshop, 2022 | 1 | 2022 |
| Performance analysis of a gas carrier using continual learning in a data stream context M Mittendorf, UD Nielsen, HB Bingham, D Gundermann, D Schmode, ... 7th Hull Performance and Insight Conference 2022, 2022 | 1 | 2022 |
| A PhD project jointly funded by A/SD/S Orients Fond and Den Danske Maritime Fond UD Nielsen, M Mittendorf | | 2023 |
| Hull and Propeller Performance Decomposition via an Adaptive Machine Learning Framework M Mittendorf, UD Nielsen, D Gundermann 8th Hull Performance & Insight Conference (HullPIC), 70-82, 2023 | | 2023 |
| Estimating Waves Through Measured Ship Responses UD Nielsen, AH Brodtkorb, T Iseki, JJ Jensen, M Mittendorf, REG Mounet, ... 8th International Workshop on Water Waves and Floating Bodies,, 2023 | | 2023 |
| On the Determination of the Relative Wave Direction based on Measured Ship Responses using Deep Multi-Task Learning M Mittendorf, UD Nielsen, HB Bingham, G Storhaug 14th Symposium on High-Performance Marine Vehicles, 96-106, 2022 | | 2022 |
Ulrik NielsenTechnical University of DenmarkCorreu electrònic verificat a dtu.dk
