Application of the grey wolf optimizer to estimate the ground surface settlement parameters based on geological conditions, tunnel geometry, and practical factors of boring machine

In this paper, grey wolf optimization (GWO) and multiple linear regression (MLR) models have been utilized to estimate the maximum surface settlement (Smax) and trough width (i) of settlement profile due to the tunnel excavation. The results show the superiority of the GWO algorithm compared to the MLR model and similar empirical models. Moreover, the importance study and the correlation matrix of the datasets reveal that thrust force and cohesion are the most important variables on Smax and i, respectively. On the other hand, the tunnel diameter and Poisson ratio are the least important variables on Smax and i, respectively .