Strength Prediction of Fiber-Reinforced Clay Soils Stabilized with Lime Using XGBoost Machine Learning - Sari-Ahmed, Billal; Benzaamia, Ali; Ghrici, Mohamed; Moghal, Arif Ali Baig (Zielona Góra: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego)
This article proposes a predictive model for the compressive strength (UCS) of lime-stabilized clay soils reinforced with polypropylene fibers (PPF) using the extreme gradient boosting (XGBoost) algorithm. The research indicates that the developed model is highly effective and can serve as a reliable tool for anticipating the UCS of these specific soils. A comparison between experimental data and model predictions suggests that it can effectively elucidate the impact of the combined effect of lime and PPF on the compressive strength of clay soils, thus avoiding the need for new experiments to formulate new compositions.
Keywords: clayey soils; lime; polypropylene fibers; unconfined compressive strength (UCS); XGBoost algorithm