Linear and Non-Linear Regression Analysis on the Prediction of Compressive Strength of Sodium Hydroxide Pre-Treated Crumb Rubber Concrete

Abstract

This research focuses on dataset development using NaOH treatment period (NaTP), NaOH concentration (NaCon), coarse aggregates (gravel), fine aggregates (sand), water, water–cement ratio (w/c), crumb rubber percentage (CR%), and equations to predict the CS of concrete. The criteria for the model accuracy included the coefficient of regression (R2), mean absolute error (MAE), and root mean square deviation (RMSE). In this study, Multiple Non-Linear Regression (MNLR) performed better compared to Multiple Linear Regression (MLR). The MNLR values obtained for R2, MAE, and RMSE were 0.88, 4.64, and 6.15; and the MLR values were 0.82, 5.86, and 7.43 for R2, MAE, and RMSE, respectively.

Keywords

• regression analysis
• multiple linear regression
• pre-treatment
• compressive strength