Applications of machine learning methods for design and characterization of high-performance fiber-reinforced cementitious composite (HPFRCC): a review

Journal of Sustainable Cement-Based Materials, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 24

Published: Feb. 6, 2025

Language: Английский

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BIM-based parametric energy analysis of green building components for the roofs and facades

Next Sustainability, Journal Year: 2024, Volume and Issue: 5, P. 100078 - 100078

Published: Oct. 7, 2024

Language: Английский

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Predicting the impact of adding metakaolin on the flexural strength of concrete using ML classification techniques – a comparative study

Frontiers in Built Environment, Journal Year: 2024, Volume and Issue: 10

Published: Nov. 7, 2024

The structural design standards, particularly in concrete technology, heavily rely on the mechanical attributes of concrete. Utilizing dependable predictive models for these properties can minimize need extensive laboratory testing, evaluations, and experiments to acquire essential data, thereby conserving time resources. Metakaolin (MK) is frequently incorporated as an alternative Portland cement production sustainable concrete, owing its technical advantages positive environmental impact, aligning with United Nations Sustainable Development Goals (UNSDGs) aimed at achieving net-zero objectives. However, this research presents a comparative study between eight (8) ML classification techniques namely, gradient boosting (GB), CN2, naïve bayes (NB), support vector machine (SVM), stochastic descent (SGD), k-nearest neighbor (KNN), Tree random forest (RF) estimate impact adding metakaolin flexural strength considering mixture components contents age. collected data entries prediction (Ft) containing following components; contentof (C), content (MK), water (W), fine aggregates (FAg), coarse (CAg), super-plasticizer (P), curing age testing (Age) were partitioned into 80% 20% training validation sets respectively. At end model protocol, it was found that GB, SVM, KNN which produced average MSE value zero (0) showed their decisive ability predict mixed (Ft). This outcome agrees previous reports literatures; however work Shah et al. happens be closest terms used mixes application learning techniques. It present work’s outperformed those presented by Hence reported paper show potentials applied MK optimal strength.

Language: Английский

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Technical insights of clean and sustainable photocatalytic concrete: A scientometric analysis–aided review

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 30, 2024

Language: Английский

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