About this document

Markun A 31102025 Js RR 145474 by kulkarnimaruti2 is a document available to read on EtoBox.

The study investigates the use of machine learning methods, specifically Multiple Linear Regression (MLR), Support Vector Regression (SVR), Multivariate Adaptive Regression Splines (MARS), and Random Forest (RF), to estimate the Soaked California Bearing Ratio (CBR) of soil. Using a dataset of 15 observations, the models were evaluated based on statistical performance metrics, with MLR demonstrating superior accuracy in both training and testing sets. This research highlights the potential of machine learni

Author

kulkarnimaruti2

Language

EN