AI predicts wind-uplift resistance of solar PV piles

AI Summary

Researchers in Iran developed an interpretable artificial neural network to predict the wind-uplift resistance of solar photovoltaic steel piles. The AI model achieved strong accuracy and identifies key soil and pile characteristics influencing structural stability in utility-scale PV projects.

Researchers in Iran have developed an interpretable artificial neural network to predict the uplift capacity of driven steel piles used in utility-scale PV projects. The model achieved a mean absolute percentage error of 7.63%, with pile penetration rate and soil friction angle emerging as the most influential predictors. The post AI predicts wind-uplift resistance of solar PV piles appeared first on pv magazine Global.