(untitled) (Rudarsko-geološko-naftni zbornik, 2018)
According to underground constructions development and their highly cost process, accurate assessment and prevention of probable risks are significant. Different methods have been developed to assess underground constructions. In this paper, it is aim to develop a new soft computing model to evaluate the tunnel support system. Firstly, numerical analysis was performed using the explicit finite difference model by FLAC2D software to excavate sequence model and support system installation. Design loads including the axial force, moment, and shear force were calculated for some important points of support system including the crown, middle of bottom and the side walls. In order to stability analysis of support system, the section points were evaluated into 3 clusters by Artificial Bee Colony as meta-heuristic algorithm and K-means algorithm in Matlab software. The results of clustering were compared by safety factor of support system. The results indicated that the section points that are in cluster 1 have lower safety factor than cluster 3 and 2, respectively. It concluded that the Artificial Bee Colony can be reliability used to initial assessment of tunnel support systems based on axial force, moment, and shear force.