Metaheuristic algorithms have gradually become the mainstream way to solve complex
optimization problems with their streamlined structure and robust performance. Innovative …

Compressive strength (CS) is the maximum resistance of concrete against axial
compressive loading in standard conditions. Estimation of this parameter is essential for the …

Traditional methods for designing concrete mixtures provide good results; however, they do
not guarantee the optimum composition. Consequently, applying operational research …

In the present study, six meta-heuristic schemes are hybridized with artificial neural network
(ANN), adaptive neuro-fuzzy interface system (ANFIS), and support vector machine (SVM) …

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 …

Due to the benefits of the early prediction of concrete slump, introducing an efficient model
for this purpose is of great importance. Considering this motivation, four strong metaheuristic …

Concrete is a most utilized material in the construction industry that have main components.
The strength of concrete can be improved by adding some admixtures. Evaluating the …

The advent of new data-mining techniques and, more recently, swarm-based optimization
algorithms have antiquated traditional models in the field of energy performance analysis …

Splitting tensile strength (STS) is an important mechanical parameter of concrete. This study
offers novel methodologies for the early prediction of this parameter. Artificial neural network …

Many environmental issues have arisen as a result of the widespread usage of concrete,
which has led to a reduction of river sand. The excessive extraction of river sand has led to …