Principal component analysis (PCA) is often applied for analyzing data in the most diverse
areas. This work reports, in an accessible and integrated manner, several theoretical and …

The paper explores the usefulness of hybridizing two distinct nature inspired computational
intelligence techniques viz., Artificial Neural Networks (ANN) and Genetic Algorithms (GA) …

High-performance concrete (HPC) is a highly complex material, which makes modeling its
behavior a very difficult task. Several studies have independently shown that the slump flow …

An artificial neural network (ANN) is presented to predict a 28-day compressive strength of a
normal and high strength self compacting concrete (SCC) and high performance concrete …

In this study, gene expression programming (GEP) is utilized to derive a new model for the
prediction of compressive strength of high performance concrete (HPC) mixes. The model is …

In this study, an artificial neural network model for compressive strength of self-compacting
concretes (SCCs) containing mineral additives and polypropylene (PP) fiber exposed to …

This study attempts to develop a machine learning model to predict the concrete slump as a
function of mix proportions, taking advantage of the 3599 observations of industrially …

Utilizing bentonite in composites such as concrete mixture is one of the practical approaches
for adsorption of heavy metals. The mixture of bentonite and normal concrete is known as …

Digital transformation of concrete technology is one of the current “hot topics” tackled by both
academia and industry. The final goal is to fully integrate the already existing advanced …

Concrete is the most used construction material for a century. After casting and setting,
concrete shows various dimensional physical and mechanical evolutions, of which drying. It …