Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …

This study offers a complete analysis of the use of deep learning or machine learning, as
well as precise recommendations on how these methods could be used in the creation of …

In the present study, a total of 360 FE analyses were carried out on tubular X-joints
strengthened with collar plates under brace tension under laboratory testing conditions (20° …

The design process of thin-walled structural members is highly complex due to the possible
occurrence of multiple instabilities. This research therefore aimed to develop machine …

Cold-formed steel (CFS) purlins and studs with staggered web perforations have been used
in construction to improve the thermal efficiency of buildings. The perforations adversely …

In this paper, a machine-learning optimisation framework for cold-formed steel (CFS) face-to-
face built-up columns was proposed using Deep Belief Network (DBN) and Genetic …

This paper presents a novel fuzzy adaptive jellyfish search-optimized stacking system (FAJS-
SS) that integrates the jellyfish search (JS) optimizer, the fuzzy adaptive (FA) logic controller …

High strength steel is regarded as a promising construction material due to its superior
mechanical properties. However, the codified failure load predictions for high strength steel …

This paper presents a numerical investigation of the ultimate limit state of imperfect columns
under axial compression; the columns are made of stainless steel with a circular hollow …

High strength steel has been attracting attention in the building industry due to its superior
mechanical properties. The accurate design of high strength steel structures is crucial to …