Assessing the impact of inertial load on the buckling behavior of piles with large slenderness ratios in liquefiable deposits

Predictive analysis of concrete slump using a stochastic search-consolidated neural network

“…Concrete is known as a suitable construction material that has been used in various projects worldwide [ [1] , [2] , [3] , [4] , [5] ]. The prediction of concrete parameters such as compressive strength (CS) is very important and can lead to reducing the time and cost of a project [ 6 ].…”

Integrated machine learning for modeling bearing capacity of shallow foundations

“…A significant portion of recent literature highlights the positive effect of newly developed technology on diverse engineering domains 1 – 5 . These developments include new approaches, devices, and software that assist experts towards facilitating data acquisition, simulation, and eventually solving complex engineering problems 6 – 10 .…”

Design optimization of irregularity RC structure based on ANN-PSO

“…Laboratory studies allow the evaluation of concrete properties, material properties analysis, investigation of failure mechanisms, simulation of various environmental conditions like extreme temperatures and loading conditions, and development and assessment of different structural elements [ [15] , [16] , [17] , [18] , [19] ]. Despite the mentioned advantages of experimental works, they suffer from scale limitations and are costly and time-consuming [ 20 ]. Nowadays, significant advancements have been made in the field of structural design using numerical analysis and finite element methods (FEM) that enable engineers to accurately simulate the three-dimensional behavior of large-scale structures [ 21 , 22 ].…”