Regression Analysis Following Levenberg - Marquardt Algorithm to Estimate Elastic Modulus of Sandy Clay Embankment

Abstract

Road design must consider the factors affecting the elastic modulus of the cohesive soil used for the roadbed. Accurate determination of the elastic modulus of the pavement will help calculate properly the deformation of the pavement and prevent the appearance of cracks in the pavement; especially when the roadbed is flooded. This study is based on the laboratory data, using Levenberg-Marquardt algorithm and building a program for regression analysis, proposing the coefficients to estimate the elastic modulus of the roadbed. From the research results obtained, the way to choose the adjustment coefficients has been improved by adding the coefficient µ, the Levenberg-Marquardt algorithm has solved the problem with only 1,351 iterations, proving the simplicity and efficiency to solve the problem of nonlinear minimum squares that sometimes cannot be solved by the Gauss-Newton method. This algorithm is applied to regression analysis of experimental results, adding the values of coefficients a 9 and a 10 to propose the values of the remaining coefficients a n and b n of the formula Dong-Gyou Kim, MS, 2004 with correlation coefficient R 2 is 0.8929. As a result, the article proposes the appropriate value of the regression coefficients into the formula to estimate the elastic modulus of the sandy clay embankment according to the humidity and material characteristics of land, instead of using the Benkelman method which is time-consuming, expensive and difficult to implement.