14 citations as recorded by crossref.

1. Data-driven farm-wide fatigue estimation on jacket-foundation OWTs for multiple SHM setups F. d N Santos et al. 10.5194/wes-7-299-2022
2. Virtual sensors for wind turbines with machine learning‐based time series models N. Dimitrov & T. Göçmen 10.1002/we.2762
3. Angle Calculus-Based Thrust Force Determination on the Blades of a 10 kW Wind Turbine J. Dorrego-Portela et al. 10.3390/technologies12020022
4. Impact of calibrated soil-monopile-interaction model on resonance frequencies C. Sastre Jurado et al. 10.1088/1742-6596/2265/3/032098
5. Inverse estimation of breaking wave loads on monopile wind turbines K. Maes et al. 10.1016/j.oceaneng.2018.05.049
6. Machine Learning Solutions for Offshore Wind Farms: A Review of Applications and Impacts M. Masoumi 10.3390/jmse11101855
7. SCADA-based neural network thrust load model for fatigue assessment: cross validation with in-situ measurements F. Santos et al. 10.1088/1742-6596/1618/2/022020
8. Probabilistic surrogates for flow control using combined control strategies C. Debusscher et al. 10.1088/1742-6596/2265/3/032110
9. Load identification of a 2.5 MW wind turbine tower using Kalman filtering techniques and BDS data D. Wei et al. 10.1016/j.engstruct.2023.115763
10. Wireless High-Resolution Acceleration Measurements for Structural Health Monitoring of Wind Turbine Towers B. Wondra et al. 10.1007/s41688-018-0029-y
11. Feature selection techniques for modelling tower fatigue loads of a wind turbine with neural networks A. Movsessian et al. 10.5194/wes-6-539-2021
12. Indirect load measurement method and experimental verification of floating offshore wind turbine X. Feng et al. 10.1016/j.oceaneng.2024.117734
13. Probabilistic temporal extrapolation of fatigue damage of offshore wind turbine substructures based on strain measurements C. Hübler & R. Rolfes 10.5194/wes-7-1919-2022
14. Feature Selection Algorithms for Wind Turbine Failure Prediction P. Marti-Puig et al. 10.3390/en12030453