A Multivariate Adaptive Regression Spline Approach for Prediction of Maximum Shear Modulus and Minimum Damping Ratio

Abstract

This study uses multivariate adaptive regression spline (MARS) for determination of maximum shear modulus (G max ) and minimum damping ratio (ξ min ) of synthetic reinforced soil. MARS employs confining pressure (σ, psi), rubber (r, %) and sand (s, %) as input variables. The outputs of the MARS are G max and ξ min . The developed MARS gives equations for determination of G max and ξ min . The results of MARS have been compared with the adaptive neuro-fuzzy inference system (ANFIS), multi-layer perception (MLP) and multiple regression analysis method (MRM). A sensitivity analysis has been also carried out to determine the effect of each input variable on G max and ξ min . This study shows that the developed MARS is a robust model for prediction of G max and ξ min .