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 …

Estimating compressive strength of concrete using neural electromagnetic field optimization

MR Akbarzadeh, H Ghafourian, A Anvari… - Materials, 2023 - mdpi.com
Concrete compressive strength (CCS) is among the most important mechanical
characteristics of this widely used material. This study develops a novel integrative method …

Gene expression programming (GEP) modelling of sustainable building materials including mineral admixtures for novel solutions

DPN Kontoni, KC Onyelowe, AM Ebid, H Jahangir… - Mining, 2022 - mdpi.com
In this study, the employment of the gene expression programming (GEP) technique in
forecasting models on sustainable construction materials including mineral admixtures and …

Mapping the strength of agro-ecological lightweight concrete containing oil palm by-product using artificial intelligence techniques

A Ashrafian, E Panahi, S Salehi, M Karoglou… - Structures, 2023 - Elsevier
The critical challenge for the cement production industry is the high emission of greenhouse
gases. For the sustainability in a cycling economy context civil and environmental engineers …

Development of novel design strength model for sustainable concrete columns: A new machine learning-based approach

MJ Munir, SMS Kazmi, YF Wu, X Lin… - Journal of Cleaner …, 2022 - Elsevier
Billions of tons of construction and demolition (C&D) waste generation is causing global
environmental crises. The application of C&D waste in concrete columns is a sustainable …

A novel hybrid adaptive boosting approach for evaluating properties of sustainable materials: A case of concrete containing waste foundry sand

AR Ghanizadeh, AT Amlashi, S Dessouky - Journal of Building Engineering, 2023 - Elsevier
Ensemble learning (EL) has gained popularity in recent investigations because of its higher
prediction accuracy than conventional machine learning (ML) methods. Regressors and EL …

Evaluation of water quality indexes with novel machine learning and SHapley Additive ExPlanation (SHAP) approaches

A Aldrees, M Khan, ATB Taha, M Ali - Journal of Water Process …, 2024 - Elsevier
Water quality indexes (WQI) are pivotal in assessing aquatic systems. Conventional
modeling approaches rely on extensive datasets with numerous unspecified inputs, leading …

Supplementary cementitious materials in blended cement concrete: Advancements in predicting compressive strength through machine learning

F Aslam, MZ Shahab - Materials Today Communications, 2024 - Elsevier
The increasing utilization of Portland cement raises environmental concerns. Thus, leading
to the exploration of supplementary cementitious materials (SCMs) as alternatives to use in …

Development of a novel compressive strength design equation for natural and recycled aggregate concrete through advanced computational modeling

MJ Munir, SMS Kazmi, YF Wu, X Lin… - Journal of Building …, 2022 - Elsevier
Owing to the variations in the recycled coarse aggregates (RCA) characteristics, the
compressive strength prediction of recycled aggregate concrete (RAC) is a complex …

Green mix design of rubbercrete using machine learning-based ensemble model and constrained multi-objective optimization

EM Golafshani, M Arashpour, A Kashani - Journal of Cleaner Production, 2021 - Elsevier
Although the use of waste rubber (WR) in concrete can alleviate some negatives effect on
sustainability, it can decrease the compressive strength (CS) of the produced rubbercrete …