In the present study, 20 models were developed using gene expression programming (GEP) to predict the compressive strength and mass loss of geopolymer mortar (GPM) containing recycled concrete aggregate (RCA) exposed to ...

In this study an Artificial Neural Network (ANN) model was used to predict the Unconfined Compressive Strength (UCS) of Kaolin clay mixed with pond ash, rice husk ash and cement content model under different curing period. ...

Inaccurate cost estimates have substantial effects on the final cost of construction projects and erode profits. Cost estimation at conceptual phase is a challenge as inadequate information is available. For this purpose, ...

Seismic vulnerability means the inability of historical and monumental buildings to withstand the effects of seismic forces. This article presents a classification model to specify the damage state of the Reinforced Concrete ...

A predictive model based on the artificial neural network (ANN) was generated to assess the compressive strength of Mortar incorporating metakaolin (MK). For this purpose, a database was gathered from different works of ...

This research presents the optimization techniques for reinforced concrete waffle slab design because the code cannot provide an efficient and optimum design. Waffle slab is mostly used where there is necessity to avoid ...

The main purpose of the current study was to formulate an empirical expression for predicting the axial compression capacity and axial strain of concrete-filled plastic tubular specimens (CFPT) using the artificial neural ...