Machine learning for structural engineering: A state-of-the-art review
HT Thai - Structures, 2022 - Elsevier
Abstract Machine learning (ML) has become the most successful branch of artificial
intelligence (AI). It provides a unique opportunity to make structural engineering more …
intelligence (AI). It provides a unique opportunity to make structural engineering more …
A review on material mix proportion and strength influence parameters of geopolymer concrete: Application of ANN model for GPC strength prediction
Concrete is a combination of cement, sand, aggregate, and water. Cement manufacturing
causes the generation of various gases, mainly greenhouse gases like CO 2 in the …
causes the generation of various gases, mainly greenhouse gases like CO 2 in the …
[HTML][HTML] A novel approach to explain the black-box nature of machine learning in compressive strength predictions of concrete using Shapley additive explanations …
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 …
the compressive strength of concrete. Despite higher accuracy, previous ML models failed to …
[HTML][HTML] Interpretable Ensemble-Machine-Learning models for predicting creep behavior of concrete
This study aims to provide an efficient and accurate machine learning (ML) approach for
predicting the creep behavior of concrete. Three ensemble machine learning (EML) models …
predicting the creep behavior of concrete. Three ensemble machine learning (EML) models …
[HTML][HTML] Data-driven compressive strength prediction of steel fiber reinforced concrete (SFRC) subjected to elevated temperatures using stacked machine learning …
Experimental studies using a substantial number of datasets can be avoided by employing
efficient methods to predict the mechanical properties of construction materials. The …
efficient methods to predict the mechanical properties of construction materials. The …
[HTML][HTML] To predict the compressive strength of self compacting concrete with recycled aggregates utilizing ensemble machine learning models
J de-Prado-Gil, C Palencia, N Silva-Monteiro… - Case Studies in …, 2022 - Elsevier
This study aims to apply machine learning methods to predict the compression strength of
self-compacting recycled aggregate concrete. To obtain this goal, the ensemble methods …
self-compacting recycled aggregate concrete. To obtain this goal, the ensemble methods …
[HTML][HTML] Data-driven based estimation of waste-derived ceramic concrete from experimental results with its environmental assessment
Q Chang, L Liu, MU Farooqi, B Thomas… - Journal of Materials …, 2023 - Elsevier
The significant requirement for natural resources, specifically as ingredients of cement, is
accelerating due to the considerable growth of the construction sector. Further, cement …
accelerating due to the considerable growth of the construction sector. Further, cement …
Modeling strength characteristics of basalt fiber reinforced concrete using multiple explainable machine learning with a graphical user interface
This study investigated the importance of applying explainable artificial intelligence (XAI) on
different machine learning (ML) models developed to predict the strength characteristics of …
different machine learning (ML) models developed to predict the strength characteristics of …
Integrating feature engineering, genetic algorithm and tree-based machine learning methods to predict the post-accident disability status of construction workers
The construction industry is among the riskiest industries around the world. Hence, the
preliminary studies exploring the consequences of occupational accidents have received …
preliminary studies exploring the consequences of occupational accidents have received …
[HTML][HTML] Testing and modeling methods to experiment the flexural performance of cement mortar modified with eggshell powder
Sustainable development might be promoted if waste eggshells are used in cement-based
materials (CBMs) by decreasing waste disposal problems, CO 2 emissions, and material …
materials (CBMs) by decreasing waste disposal problems, CO 2 emissions, and material …