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

Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …

Soft computing (SC), due to its high abilities to solve the complex problems with uncertainty
and multiple parameters, has been widely investigated and used, especially in structural …

Nowadays, strengthening of reinforced concrete structures with a new class of sustainable
materials is the possible solution to retrofit the aged deteriorated structures. It is difficult to …

Abstract The Externally Bonded Reinforcement on Grooves (EBROG) method represents an
advancement in externally bonded reinforcement (EBR) techniques, specifically addressing …

Stock market trends can be affected by external factors such as public sentiment and
political events. The goal of this research is to find whether or not public sentiment and …

Developments in fiber-reinforced polymer (FRP) composite materials have created a huge
impact on civil engineering techniques. Bonding properties of FRP led to its wide usage with …

This study aims to investigate the performance of three advanced data-driven models,
namely multivariate adaptive regression spline (MARS), artificial neural network (ANN), and …

Population growth and increased demand for construction have reduced and destroyed the
available natural resources. In the meantime, the destruction and demolish of older …

This study employs soft computing techniques, including artificial neural network (ANN)
models and gene expression programming (GEP), to enhance the prediction of ultimate load …