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 …

Compressive Strength of Fly‐Ash‐Based Geopolymer Concrete by Gene Expression Programming and Random Forest

MA Khan, SA Memon, F Farooq… - Advances in Civil …, 2021 - Wiley Online Library
Fly ash (FA) is a residual from thermal industries that has been effectively utilized in the
production of FA‐based geopolymer concrete (FGPC). To avoid time‐consuming and costly …

Comparative study of advanced computational techniques for estimating the compressive strength of UHPC

M Khan, J Lao, JG Dai - Journal of …, 2022 - jacf.sfulib3.publicknowledgeproject …
The effect of raw materials on the compressive strength of concrete is a complex process,
especially in the case of ultra-high-performance concrete (UHPC), where a higher number of …

Prediction of chloride diffusivity in concrete using artificial neural network: Modelling and performance evaluation

Q Liu, MF Iqbal, J Yang, X Lu, P Zhang… - Construction and Building …, 2021 - Elsevier
Chloride ingression is the main reason for causing durability degradation of reinforced
concrete (RC) structures. In this study, the distinguishing features of artificial neural network …

Predictive modeling of swell-strength of expansive soils using artificial intelligence approaches: ANN, ANFIS and GEP

FE Jalal, Y Xu, M Iqbal, MF Javed, B Jamhiri - Journal of Environmental …, 2021 - Elsevier
This study presents the development of new empirical prediction models to evaluate swell
pressure and unconfined compression strength of expansive soils (P s UCS-ES) using three …

[HTML][HTML] A comparative study of random forest and genetic engineering programming for the prediction of compressive strength of high strength concrete (HSC)

F Farooq, M Nasir Amin, K Khan, M Rehan Sadiq… - Applied Sciences, 2020 - mdpi.com
Supervised machine learning and its algorithm is an emerging trend for the prediction of
mechanical properties of concrete. This study uses an ensemble random forest (RF) and …

[HTML][HTML] Prediction of compressive strength of fly ash based concrete using individual and ensemble algorithm

A Ahmad, F Farooq, P Niewiadomski, K Ostrowski… - Materials, 2021 - mdpi.com
Machine learning techniques are widely used algorithms for predicting the mechanical
properties of concrete. This study is based on the comparison of algorithms between …

Influence of the incorporation of recycled coarse aggregate on water absorption and chloride penetration into concrete

J Bao, S Li, P Zhang, X Ding, S Xue, Y Cui… - Construction and Building …, 2020 - Elsevier
Abstract Knowledge of the transport properties for recycled aggregate concrete (RAC)
exposed to chloride environment plays a critical role in assessing its durability and …

[HTML][HTML] Predicting compressive strength of eco-friendly plastic sand paver blocks using gene expression and artificial intelligence programming

B Iftikhar, SC Alih, M Vafaei, MF Javed, MF Rehman… - Scientific reports, 2023 - nature.com
Plastic sand paver blocks provide a sustainable alternative by using plastic waste and
reducing the need for cement. This innovative approach leads to a more sustainable …

Developing a sustainable concrete incorporating bentonite clay and silica fume: Mechanical and durability performance

M Ashraf, MF Iqbal, M Rauf, MU Ashraf, A Ulhaq… - Journal of Cleaner …, 2022 - Elsevier
The use of supplementary cementitious materials (SCMs) can improve the properties of
concrete, reduce pressure on natural resources and CO 2 emissions. However, certain …