NATURAL GRADIENT BOOSTING FOR PROBABILISTIC PREDICTION OF SOAKED CBR VALUES USING AN EXPLAINABLE ARTIFICIAL INTELLIGENCE APPROACH

Natural Gradient Boosting for Probabilistic Prediction of Soaked CBR Values Using an Explainable Artificial Intelligence Approach

The California bearing ratio (CBR) value of subgrade is the most used parameter for dimensioning flexible and rigid pavements.The test for determining the CBR value is typically conducted under soaked conditions and is costly, labour-intensive, and time-consuming.Machine learning (ML) techniques have been The Slacker Pant recently implemented in en

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