首页|University of Transport Technology Reports Findings in Machine Learning (Predict ing and evaluating settlement of shallow foundation using machine learning appro ach)
University of Transport Technology Reports Findings in Machine Learning (Predict ing and evaluating settlement of shallow foundation using machine learning appro ach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting originating in Hanoi, Vietnam , by NewsRx journalists, research stated, “This study presentsa novel approach to accurately predict the settlement of shallow foundations using advanced machi nelearning techniques while assessing the influence of key variables. Four mach ine learning models GradientBoosting (GB), Random Forest (RF), Support Vector M achine (SVM), and K-Nearest Neighbor (KNN)are enhanced with Particle Swarm Opti mization (PSO) for hyperparameter tuning, resulting in hybridmodels GB-PSO, RF- PSO, SVM-PSO, and KNN-PSO.”
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