Parameter Determination Method of Soil Constitutive Model Based on Machine Learning

Abstract

In order to better determine the model parameters and improve the safety and stability of construction, an optimized identification method of constitutive model parameters with improved RCGA is proposed by combining the current optimization theory. The experimental results indicate that the improved RCGA algorithm proposed in the study has stronger recognition capabilities and optimization effects than the traditional NSGA-II algorithm and determine the parameters of the constitutive model more accurately. Moreover, it is found that the parameters obtained by the proposed improved algorithm have validity and accuracy, when parameter ${P_0}^{\prime }=50$  kPa, comparing the obtained optimal parameters with the real laboratory clay parameters.