Predicting California bearing ratio of HARHA-treated expansive soils using Gaussian process regression.

ABSTRACT: The California bearing ratio (CBR) is one of the basic subgrade strength characterization properties in road pavement design for evaluating the bearing capacity of pavement subgrade materials. In this research, a new model based on the Gaussian process regression (GPR) computing technique was trained and developed to predict CBR value of hydrated lime-activated rice husk ash (HARHA) treated soil. An experimental database containing 121 data points have been used. The dataset contains input parameters namely HARHA-a hybrid geometrical binder, liquid limit, plastic limit, plastic index, optimum moisture content, activity and maximum dry density while the output parameter for the model is CBR. The performance of the GPR model is assessed using statistical parameters, including the coefficient

SUBMITTER: Ahmad M 

PROVIDER: S-EPMC10442396 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature