Predicting concrete compressive strength using hybrid ensembling of surrogate machine learning models
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 …
predicting the compressive strength (CS) of concrete, an important parameter used for …
Machine learning models for predicting the compressive strength of concrete containing nano silica
Experimentally predicting the compressive strength (CS) of concrete (for a mix design) is a
time-consuming and laborious process. The present study aims to propose surrogate …
time-consuming and laborious process. The present study aims to propose surrogate …
Compressive strength prediction of high-performance concrete using gradient tree boosting machine
In structural engineering, concrete compressive strength (CCS) is the most important
performance parameter for designing the conventional concrete and high-performance …
performance parameter for designing the conventional concrete and high-performance …
A sensitivity and robustness analysis of GPR and ANN for high-performance concrete compressive strength prediction using a Monte Carlo simulation
This study aims to analyze the sensitivity and robustness of two Artificial Intelligence (AI)
techniques, namely Gaussian Process Regression (GPR) with five different kernels …
techniques, namely Gaussian Process Regression (GPR) with five different kernels …
Predicting the compressive strength of concrete from its compositions and age using the extreme gradient boosting method
The uniaxial compressive strength (UCS) is one of the most important mechanical properties
of concrete. This paper aims to demonstrate that the UCS of concrete can be accurately …
of concrete. This paper aims to demonstrate that the UCS of concrete can be accurately …
[HTML][HTML] Nonlinear finite element and analytical modelling of reinforced concrete filled steel tube columns under axial compression loading
Local buckling of steel and excessive spalling of concrete have necessitated the need for
the evaluation of reinforced concrete columns subjected to axial compression loading. Thus …
the evaluation of reinforced concrete columns subjected to axial compression loading. Thus …
Shear capacity prediction of slender reinforced concrete structures with steel fibers using machine learning
Shear failure in reinforced concrete beams poses a critical safety issue since it may occur
without any prior signs of damage in some cases. Many of the existing shear design …
without any prior signs of damage in some cases. Many of the existing shear design …
An insight into tetracycline photocatalytic degradation by MOFs using the artificial intelligence technique
M Gheytanzadeh, A Baghban, S Habibzadeh… - Scientific Reports, 2022 - nature.com
Tetracyclines (TCs) have been extensively used for humans and animal diseases treatment
and livestock growth promotion. The consumption of such antibiotics has been ever-growing …
and livestock growth promotion. The consumption of such antibiotics has been ever-growing …
Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches
Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …
Retracted Article: Novel hybrid QSPR-GPR approach for modeling of carbon dioxide capture using deep eutectic solvents
I Salahshoori, A Baghban, A Yazdanbakhsh - RSC advances, 2023 - pubs.rsc.org
In recent years, deep eutectic solvents (DESs) have garnered considerable attention for their
potential in carbon capture and utilization processes. Predicting the carbon dioxide (CO2) …
potential in carbon capture and utilization processes. Predicting the carbon dioxide (CO2) …