A critical review on modeling and prediction on properties of fresh and hardened geopolymer composites

P Zhang, Y Mao, W Yuan, J Zheng, S Hu… - Journal of Building …, 2024 - Elsevier
Geopolymer is an environmentally friendly material that is recognized as a potential
alternative binder to ordinary Portland cement. However, accurate prediction of the …

[HTML][HTML] The use of machine learning techniques to investigate the properties of metakaolin-based geopolymer concrete

SAE Afzali, MA Shayanfar, M Ghanooni-Bagha… - Journal of Cleaner …, 2024 - Elsevier
The construction industry significantly contributes to global greenhouse gas emissions,
highlighting the imperative for develo** environmentally friendly construction materials …

Estimation of strength, rheological parameters, and impact of raw constituents of alkali-activated mortar using machine learning and SHapely Additive exPlanations …

S Nazar, J Yang, XE Wang, K Khan, MN Amin… - … and Building Materials, 2023 - Elsevier
One-part alkali-activated material (AAM) is a new eco-friendly developed low-carbon binder
that utilizes alkaline activators in solid form. This study deals with the experimental synthesis …

Prediction of compressive strength of high-volume fly ash self-compacting concrete with silica fume using machine learning techniques

S Kumar, R Kumar, B Rai, P Samui - Construction and Building Materials, 2024 - Elsevier
The quality and composition of the components in Self-Compacting Concrete (SCC)
determine its compressive strength; however, determining these complex relationships …

Development of compressive strength prediction platform for concrete materials based on machine learning techniques

K Liu, L Zhang, W Wang, G Zhang, L Xu, D Fan… - Journal of Building …, 2023 - Elsevier
With the continuous development of artificial intelligence, machine learning (ML), as an
important branch, is used to promote the digitalization of concrete. Considering that the …

Prediction of masonry prism strength using machine learning technique: Effect of dimension and strength parameters

N Sathiparan, P Jeyananthan - Materials today communications, 2023 - Elsevier
The compressive strength of masonry must be determined to design masonry constructions.
Although the compressive strength of masonry mostly depends on the compressive strength …

[HTML][HTML] Enhancing compressive strength prediction in self-compacting concrete using machine learning and deep learning techniques with incorporation of rice husk …

MS Mahmood, A Elahi, O Zaid, Y Alashker… - Case Studies in …, 2023 - Elsevier
Focusing on sustainable development, the demand for alternative materials in concrete,
especially for Self-Compacting Concrete (SCC), has risen due to excessive cement usage …

Application of machine learning boosting and bagging methods to predict compressive and flexural strength of marble cement mortar

Z Chen - Materials Today Communications, 2024 - Elsevier
Compressive (CS) and flexural strength (FS) of sustainable mortar made from waste
materials were estimated using machine learning (ML) tools. Ensemble ML techniques …

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 …

A comparative study of prediction models for alkali-activated materials to promote quick and economical adaptability in the building sector

SU Arifeen, MN Amin, W Ahmad, F Althoey, M Ali… - … and Building Materials, 2023 - Elsevier
Alkali-activated materials (AAMs) have recently gained attention as potentially useful
alternative binders that can reduce carbon dioxide emissions initiated by the production of …