Resilient modulus ((Formula presented.)) plays the most critical role in the evaluation and design of flexible pavement foundations. (Formula presented.) is utilised as the principal parameter for representing stiffness and behaviour of flexible pavement foundation in experimental and semi-empirical approaches. To determine (Formula ...
Resilient modulus ((Formula presented.)) plays the most critical role in the evaluation and design of flexible pavement foundations. (Formula presented.) is utilised as the principal parameter for representing stiffness and behaviour of flexible pavement foundation in experimental and semi-empirical approaches. To determine (Formula presented.), cyclic triaxial compressive experiments under different confining pressures and deviatoric stresses are needed. However, such experiments are costly and time-consuming. In the present study, an extreme gradient boosting-based ((Formula presented.)) model is presented for predicting the resilient modulus of flexible pavement foundations. The model is optimised using four different optimisation methods (particle swarm optimisation ((Formula presented.)), social spider optimisation ((Formula presented.)), sine cosine algorithm ((Formula presented.)), and multi-verse optimisation ((Formula presented.))) and a database collected from previously published technical literature. The outcomes present that all developed designs have good workability in estimating the (Formula presented.) of flexible pavement foundation, but the (Formula presented.) models have the best prediction accuracy considering both training and testing datasets.