Machine and deep learning methods for concrete strength Prediction: A bibliometric and content analysis review of research trends and future directions

R Kumar, E Althaqafi, SGK Patro, V Simic… - Applied Soft …, 2024 - Elsevier
This review paper provides a detailed evaluation of the existing landscape and future trends
in applying machine learning and deep learning approaches for predicting concrete strength …

Comparison of various machine learning algorithms used for compressive strength prediction of steel fiber-reinforced concrete

SS Pakzad, N Roshan, M Ghalehnovi - Scientific Reports, 2023 - nature.com
Adding hooked industrial steel fibers (ISF) to concrete boosts its tensile and flexural strength.
However, the understanding of ISF's influence on the compressive strength (CS) behavior of …

[HTML][HTML] Optimizing compressive strength prediction models for rice husk ash concrete with evolutionary machine intelligence techniques

MN Amin, W Ahmad, K Khan, AF Deifalla - Case Studies in Construction …, 2023 - Elsevier
This research intended to increase the understanding of using modern machine intelligence
techniques, including multi-expression programming (MEP) and gene expression …

[HTML][HTML] Application of metaheuristic optimization algorithms in predicting the compressive strength of 3D-printed fiber-reinforced concrete

M Alyami, M Khan, MF Javed, M Ali… - Developments in the …, 2024 - Elsevier
In recent years, the construction industry has been striving to make production faster and
handle more complex architectural designs. Waste reduction, geometric freedom, lower …

Development of the new prediction models for the compressive strength of nanomodified concrete using novel machine learning techniques

S Nazar, J Yang, W Ahmad, MF Javed… - Buildings, 2022 - mdpi.com
Concrete is a heterogeneous material that is extensively used as a construction material.
However, to improve the toughness and mechanical properties of concrete, various …

Evaluating the strength and impact of raw ingredients of cement mortar incorporating waste glass powder using machine learning and SHapley additive ExPlanations …

HA Alkadhim, MN Amin, W Ahmad, K Khan, S Nazar… - Materials, 2022 - mdpi.com
This research employed machine learning (ML) and SHapley Additive ExPlanations (SHAP)
methods to assess the strength and impact of raw ingredients of cement mortar (CM) …

A comprehensive GEP and MEP analysis of a cement-based concrete containing metakaolin

MI Faraz, SU Arifeen, MN Amin, A Nafees, F Althoey… - Structures, 2023 - Elsevier
Due to the detrimental environmental consequence of cement formation, studies has
concentrated on decreasing the environmental influence and expense of cement containing …

[HTML][HTML] Predicting the crack width of the engineered cementitious materials via standard machine learning algorithms

X Yuan, Q Cao, MN Amin, A Ahmad, W Ahmad… - Journal of Materials …, 2023 - Elsevier
This study aims to develop various machine learning (ML) models to investigate the self-
healing capacity of engineered cementitious composites (ECC) and to evaluate the effect of …

[HTML][HTML] Compressive strength prediction of sustainable concrete incorporating rice husk ash (RHA) using hybrid machine learning algorithms and parametric …

A Kashem, R Karim, P Das, SD Datta… - Case Studies in …, 2024 - Elsevier
The construction industry is making efforts to reduce the environmental impact of cement
production in concrete by incorporating alternative and supplementary cementitious …

[HTML][HTML] Estimating compressive strength of concrete containing rice husk ash using interpretable machine learning-based models

M Alyami, M Khan, AWA Hammad… - Case Studies in …, 2024 - Elsevier
The construction sector is a major contributor to global greenhouse gas emissions. Using
recycled and waste materials in concrete is a practical solution to address environmental …