Improving semi-empirical equations of ultimate bearing capacity of shallow foundations using soft computing polynomials

This study presents the ultimate bearing capacity of shallow foundations in meaningful ways and improves its semi-empirical equations accordingly. Approaches including weighted genetic programming (WGP) and soft computing polynomials (SCP) are utilized to provide accurate prediction and visible formulas/polynomials for the ultimate bearing capacity. Visible formulas facilitate parameter studies, sensitivity analysis, and applications of pruning techniques. Analytical results demonstrate that the proposed SCP is outstanding in both prediction accuracy and provides simple polynomials as well. Notably, the SCP identifies that the shearing resistance angle and foundation geometry impact on improving the Vesic's semi-empirical equations.

► Improved weighted genetic programming (WGP) and novel soft computing polynomials (SCP) are proposed.
► The ultimate bearing capacity of shallow foundations is predicted and programmed.
► The SCP is further used to improve existed semi-empirical equations.
► Visible polynomials facilitate parameter studies.
► Sensitivity analysis for parameters and pruning techniques for polynomials are investigated.