13 citations as recorded by crossref.

1. Estimation of Hub Center Loads for Individual Pitch Control for Wind Turbines Based on Tower Loads and Machine Learning S. Kiyoki et al. 10.3390/electronics13183648
2. Virtual sensing in an onshore wind turbine tower using a Gaussian process latent force model J. Bilbao et al. 10.1017/dce.2022.38
3. Farm‐wide interface fatigue loads estimation: A data‐driven approach based on accelerometers F. de N Santos et al. 10.1002/we.2888
4. Efficient fatigue damage estimation of offshore wind turbine foundation under wind-wave actions T. Li et al. 10.1016/j.jcsr.2024.108903
5. A State‐of‐Art Review on Prediction Model for Fatigue Performance of Welded Joints via Data‐Driven Method C. Feng et al. 10.1002/adem.202201430
6. 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
7. Power data integrity verification method based on chameleon authentication tree algorithm and missing tendency value X. Liu et al. 10.1515/ehs-2023-0067
8. Farm-wide virtual load monitoring for offshore wind structures via Bayesian neural networks N. Hlaing et al. 10.1177/14759217231186048
9. Predictions for Bending Strain at the Tower Bottom of Offshore Wind Turbine Based on the LSTM Model S. Lee et al. 10.3390/en16134922
10. An Overview on Structural Health Monitoring and Fault Diagnosis of Offshore Wind Turbine Support Structures Y. Yang et al. 10.3390/jmse12030377
11. Machine Learning Solutions for Offshore Wind Farms: A Review of Applications and Impacts M. Masoumi 10.3390/jmse11101855
12. Flexible multi-fidelity framework for load estimation of wind farms through graph neural networks and transfer learning G. Duthé et al. 10.1017/dce.2024.35
13. Long-term fatigue estimation on offshore wind turbines interface loads through loss function physics-guided learning of neural networks F. de N Santos et al. 10.1016/j.renene.2023.01.093