Predictive models for concrete properties using machine learning and deep learning approaches: A review

MM Moein, A Saradar, K Rahmati… - Journal of Building …, 2023‏ - Elsevier
Concrete is one of the most widely used materials in various civil engineering applications.
Its global production rate is increasing to meet demand. Mechanical properties of concrete …

Artificial intelligence, machine learning, and deep learning in structural engineering: a scientometrics review of trends and best practices

ATG Tapeh, MZ Naser - Archives of Computational Methods in …, 2023‏ - Springer
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …

[HTML][HTML] A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations …

IU Ekanayake, DPP Meddage, U Rathnayake - Case Studies in …, 2022‏ - Elsevier
Abstract Machine learning (ML) techniques are often employed for the accurate prediction of
the compressive strength of concrete. Despite higher accuracy, previous ML models failed to …

Machine learning prediction of mechanical properties of concrete: Critical review

WB Chaabene, M Flah, ML Nehdi - Construction and Building Materials, 2020‏ - Elsevier
Accurate prediction of the mechanical properties of concrete has been a concern since
these properties are often required by design codes. The emergence of new concrete …

[HTML][HTML] Hybrid data-driven approaches to predicting the compressive strength of ultra-high-performance concrete using SHAP and PDP analyses

A Kashem, R Karim, SC Malo, P Das, SD Datta… - Case Studies in …, 2024‏ - Elsevier
Ultra-high-performance concrete (UHPC) is a cutting-edge and advanced construction
material known for its exceptional mechanical properties and durability. Recently, machine …

[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 …

Revolutionizing concrete analysis: An in-depth survey of AI-powered insights with image-centric approaches on comprehensive quality control, advanced crack …

K Sarkar, A Shiuly, KG Dhal - Construction and Building Materials, 2024‏ - Elsevier
Over the last two decades, the integration of big data and deep learning technologies has
demonstrated remarkable effectiveness across various domains of civil engineering, leading …

[HTML][HTML] Predicting ultra-high-performance concrete compressive strength using gene expression programming method

H Alabduljabbar, M Khan, HH Awan, SM Eldin… - Case Studies in …, 2023‏ - Elsevier
There have been extensive experimental studies available on the composition and
characteristics of Ultra-High-Performance concrete (UHPC). However, the relation between …

Estimating compressive strength of modern concrete mixtures using computational intelligence: A systematic review

I Nunez, A Marani, M Flah, ML Nehdi - Construction and Building Materials, 2021‏ - Elsevier
The mixture proportioning of conventional concrete is commonly established using
regression analysis of experimental data. However, such traditional empirical procedures …

Machine learning framework for predicting failure mode and shear capacity of ultra high performance concrete beams

R Solhmirzaei, H Salehi, V Kodur, MZ Naser - Engineering structures, 2020‏ - Elsevier
This paper presents a data-driven machine learning (ML) framework for predicting failure
mode and shear capacity of Ultra High Performance Concrete (UHPC) beams. To this end, a …