ACP - Relations - Estimating hub-height wind speed based on a machine learning algorithm: implications for wind energy assessment
Grand challenges in the science of wind energy
Spatio-seasonal Concentrations, Source Apportionment and Assessment of Associated Human Health Risks of PM2.5-bound Polycyclic Aromatic Hydrocarbons in Delhi, India - Aerosol and Air Quality Research
Twenty‐First‐Century Changes in the Eastern Mediterranean Etesians and Associated Midlatitude Atmospheric Circulation - Dafka - 2019 - Journal of Geophysical Research: Atmospheres - Wiley Online Library
PDF) Estimating hub-height wind speed based on a machine learning algorithm: implications for wind energy assessment
Interpretable Machine Learning Approaches for Forecasting and Predicting Air Pollution: A Systematic Review - Aerosol and Air Quality Research
Magnetic Properties as a Proxy for Predicting Fine-Particle-Bound Heavy Metals in a Support Vector Machine Approach
PDF) Assessment of the wind energy resource on the coast of China based on machine learning algorithms
Chapter 6: Energy systems
Data-driven optimization of building-integrated ducted openings for wind energy harvesting: Sensitivity analysis of metamodels - ScienceDirect
Wind-Turbine and Wind-Farm Flows: A Review
ACP - Estimating hub-height wind speed based on a machine learning algorithm: implications for wind energy assessment
