Adopting Artificial Intelligence for enhancing the implementation of systemic circularity in the construction industry: A critical review
Data-driven technology such as Artificial Intelligence is considered an essential enabler of
circular economy (CE) in the building construction industry (BCI). As both AI and CE …
circular economy (CE) in the building construction industry (BCI). As both AI and CE …
Prediction of concrete and FRC properties at high temperature using machine and deep learning: a review of recent advances and future perspectives
Concrete structures when exposed to elevated temperature significantly decline their
original properties. High temperatures substantially affect the concrete physical and …
original properties. High temperatures substantially affect the concrete physical and …
[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 …
Prediction based mean-value-at-risk portfolio optimization using machine learning regression algorithms for multi-national stock markets
The future performance of stock markets is the most crucial factor in portfolio creation. As
machine learning technique is advancing, new possibilities have opened up for …
machine learning technique is advancing, new possibilities have opened up for …
[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 …
[HTML][HTML] Machine learning-driven predictive models for compressive strength of steel fiber reinforced concrete subjected to high temperatures
Steel-fiber-reinforced concrete (SFRC) has emerged as a viable and efficient substitute for
traditional concrete in the construction industry. By incorporating steel fibers into the …
traditional concrete in the construction industry. By incorporating steel fibers into the …
Artificial intelligence-based optimized models for predicting the slump and compressive strength of sustainable alkali-derived concrete
Alkali-activated materials (AAMs) are a potential class of construction materials that are well-
known for their versatility and capacity for long-term sustainability. As a result of its ability to …
known for their versatility and capacity for long-term sustainability. As a result of its ability to …
[HTML][HTML] Assessing the compressive strength of self-compacting concrete with recycled aggregates from mix ratio using machine learning approach
P Jagadesh, J de Prado-Gil, N Silva-Monteiro… - Journal of Materials …, 2023 - Elsevier
The requirement of the construction sector pushes researchers and academicians to
determine the 28-day concrete compressive strength due to less consumption of natural …
determine the 28-day concrete compressive strength due to less consumption of natural …
[HTML][HTML] Artificial intelligence-based estimation of ultra-high-strength concrete's flexural property
Abstract Advancement in Artificial Intelligence (AI) techniques and their applications in the
construction industry, particularly for predicting mechanical properties of concrete, leads to …
construction industry, particularly for predicting mechanical properties of concrete, leads to …
[HTML][HTML] Compressive strength evaluation of ultra-high-strength concrete by machine learning
In civil engineering, ultra-high-strength concrete (UHSC) is a useful and efficient building
material. To save money and time in the construction sector, soft computing approaches …
material. To save money and time in the construction sector, soft computing approaches …