Development of genetic-based models for predicting the resilient modulus of cohesive pavement subgrade soils

Abstract

The accurate determination of resilient modulus (Mr) of pavement subgrade soils is an important factor for the successful design of pavement system. The important soil property Mr is complex in nature as it is dependent on several influential factors, such as soil physical properties, applied stress conditions, and environmental conditions. The aim of this study is to explore the potential of an evolutionary algorithm, i.e., genetic algorithm (GA), and a hybrid intelligent approach combining neural network with GA (ANN-GA), to estimate the Mr of cohesive pavement subgrade soils. To achieve this aim, a reliable database containing the results of repeated load triaxial tests (RLT) and other in..