Fibre reinforced polymer (FRP) composites have been increasingly applied in engineering
structures especially for achieving high demands on structural performance, but they are …

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

Development of Foamed Concrete (FC) and incessant increases in fabrication technology
have paved the way for many promising civil engineering applications. Nevertheless, the …

This paper is devoted to the development and construction of a practical Machine Learning
(ML)-based model for the prediction of tensile strength of polymer carbon nanotube (CNTs) …

An overview of the author's works, many of which were carried out in collaboration, is
presented. The first part concerns the quantification of uncertainties for complex engineering …

Abstract A Machine Learning (ML) model based on Gaussian regression, using different
kernel functions, is introduced in this paper to assess the load-carrying capacity of square …

Polymer-assisted flocculation-dewatering of mineral processing tailings (MPT) is crucial for
its environmental disposal. To reduce the number of laboratory experiments, this study …

In this paper, an extensive simulation program is conducted to find out the optimal ANN
model to predict the shear strength of fiber-reinforced polymer (FRP) concrete beams …

Estimation of pressure drops of fresh cemented paste backfill slurry is a novel idea with great
potentials. This paper presented a hybrid machine learning (ML) method for improved …

Machine Learning (ML) has been applied widely in solving a lot of real-world problems.
However, this approach is very sensitive to the selection of input variables for modeling and …