Aquila-optimized XGBoost improves reinforced subgrade strength predictions
An Aquila-optimized XGBoost model achieved an R² of 0.980 for predicting soaked CBR in 90 geosynthetic-reinforced subgrade tests, outperforming three ...
An Aquila-optimized XGBoost model achieved an R² of 0.980 for predicting soaked CBR in 90 geosynthetic-reinforced subgrade tests, outperforming three ...
A systematic review of 111 studies shows that machine learning is rapidly becoming the design tool of choice for sustainable, ...
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© 2025 Scienmag - Science Magazine