16 citations as recorded by crossref.

1. Estimation of Planetary Boundary Layer Height From Lidar by Combining Gradient Method and Machine Learning Algorithms H. Li et al.
2. Exogenous atmospheric variables as wind speed predictors in machine learning A. Dalton & B. Bekker
3. Explainable Machine Learning (XML) to predict external wind pressure of a low-rise building in urban-like settings D. Meddage et al.
4. Enabling Virtual Met Masts for wind energy applications through machine learning-methods S. Schwegmann et al.
5. Towards Sustainable Urban Mobility: Leveraging Machine Learning Methods for QA of Meteorological Measurements in the Urban Area D. Sládek et al.
6. A review of physics-based machine learning in civil engineering S. Vadyala et al.
7. A multi-dimensional interpretable wind speed forecasting model with two-stage feature exploring B. Wu et al.
8. Physics-data dual-driven approach for structural health monitoring: A systematic review W. Long et al.
9. Assessment of hybrid machine learning algorithms using TRMM rainfall data for daily inflow forecasting in Três Marias Reservoir, eastern Brazil E. Gomaa et al.
10. Research on adaptive combined wind speed prediction for each season based on improved gray relational analysis Y. Zhu
11. Using Trees as a Natural Weather Station for Wind Pattern Forecasting Applied to Forest Firefighting V. Aires et al.
12. Estimating the urban atmospheric boundary layer height from remote sensing applying machine learning techniques G. de Arruda Moreira et al.
13. Fusing physics-inferred information from stochastic model with machine learning approaches for degradation prediction Z. Li et al.
14. On the estimation of boundary layer heights: a machine learning approach R. Krishnamurthy et al.
15. Improving Surface Wind Speed Forecasts Using an Offline Surface Multilayer Model With Optimal Ground Forcing J. Feng et al.
16. A Comprehensive Degradation Modeling Comparison From Statistical to Artificial Intelligence Models for Curing Oven Chains H. Misaii et al.