Although civil engineering problems are often characterized by significant levels of
complexity, they are generally approached and solved by combining several practitioners' …

Artificial intelligence is a branch of computer science, involved in the research, design, and
application of intelligent computer. Traditional methods for modeling and optimizing complex …

This study aims to implement a hybrid ensemble surrogate machine learning technique in
predicting the compressive strength (CS) of concrete, an important parameter used for …

Solid waste in the form of construction debris is one of the major environmental concerns in
the world. Over 20 million tons of construction waste materials are generated in Tehran each …

The use of statistical and machine learning approaches to predict the compressive strength
of concrete based on mixture proportions, on account of its industrial importance, has …

The use of silica fume as a partial replacement for Ordinary Portland Cement provides a
wide variety of benefits such as reduced pressure on natural resources, reduced CO 2 …

Geopolymer concrete is a sustainable and eco-friendly substitute for traditional OPC
(Ordinary Portland Cement) based concrete, as it reduces greenhouse gas emissions. With …

In structural engineering, concrete compressive strength (CCS) is the most important
performance parameter for designing the conventional concrete and high-performance …

This study aims to analyze the sensitivity and robustness of two Artificial Intelligence (AI)
techniques, namely Gaussian Process Regression (GPR) with five different kernels …

This paper presents an ensemble machine learning (ML) model for prediction of modulus of
elasticity (MOE) of concrete formulated using recycled concrete aggregate (RCA), in relation …