Forecasting slipform labor productivity in the construction of reinforced concrete chimneys DOI Creative Commons

Şahin Tolga Güvel

Ain Shams Engineering Journal, Journal Year: 2024, Volume and Issue: unknown, P. 103192 - 103192

Published: Nov. 1, 2024

Language: Английский

Sustainable mix design and carbon emission analysis of recycled aggregate concrete based on machine learning and big data methods DOI
Boqun Zhang, Lei Pan, X. C. Chang

et al.

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: 489, P. 144734 - 144734

Published: Jan. 1, 2025

Language: Английский

Citations

2
A Systematic Review of the Applications of AI in a Sustainable Building’s Lifecycle DOI Creative Commons
B. A. Adewale,

Vincent Onyedikachi Ene,

Babatunde Fatai Ogunbayo

et al.

Buildings, Journal Year: 2024, Volume and Issue: 14(7), P. 2137 - 2137

Published: July 11, 2024

Buildings significantly contribute to global energy consumption and greenhouse gas emissions. This systematic literature review explores the potential of artificial intelegence (AI) enhance sustainability throughout a building’s lifecycle. The identifies AI technologies applicable sustainable building practices, examines their influence, analyses implementation challenges. findings reveal AI’s capabilities in optimising efficiency, enabling predictive maintenance, aiding design simulation. Advanced machine learning algorithms facilitate data-driven analysis, while digital twins provide real-time insights for decision-making. also barriers adoption, including cost concerns, data security risks, While offers innovative solutions optimisation environmentally conscious addressing technical practical challenges is crucial its successful integration practices.

Language: Английский

Citations

12
A critical analysis of compressive strength prediction of glass fiber and carbon fiber reinforced concrete over machine learning models DOI

K. K. Yaswanth,

V. S. Vani,

Krupasindhu Biswal

et al.

Multiscale and Multidisciplinary Modeling Experiments and Design, Journal Year: 2025, Volume and Issue: 8(3)

Published: Feb. 14, 2025

Language: Английский

Citations

1
Review of empowering computer-aided engineering with artificial intelligence DOI Creative Commons

Xuwen Zhao,

X. Tong, Fangwei Ning

et al.

Advances in Manufacturing, Journal Year: 2025, Volume and Issue: unknown

Published: March 14, 2025

Language: Английский

Citations

1
Artificial Intelligence (AI) in relation to environmental life-cycle assessment, photovoltaics, smart grids and small-island economies DOI Creative Commons

Chr. Lamnatou,

Christian Cristofari,

Daniel Chemisana

et al.

Sustainable Energy Technologies and Assessments, Journal Year: 2024, Volume and Issue: 71, P. 104005 - 104005

Published: Oct. 14, 2024

Language: Английский

Citations

4
Research on 3D Printing Concrete Mechanical Properties Prediction Model Based on Machine Learning DOI Creative Commons
Yonghong Zhang, Suping Cui, Bohao Yang

et al.

Case Studies in Construction Materials, Journal Year: 2025, Volume and Issue: unknown, P. e04254 - e04254

Published: Jan. 1, 2025

Language: Английский

Citations

0
Predictive Analytics and Big Data in Forecasting Recycling Trends DOI

Aparna Unni,

Harpreet Kaur Channi

Advances in environmental engineering and green technologies book series, Journal Year: 2025, Volume and Issue: unknown, P. 177 - 210

Published: Jan. 16, 2025

Predictive analytics and big data enhance recycling by analyzing social media, sensors, municipal data. Advanced algorithms manage resource allocation operations, forecasting trends from population growth economic factors. Machine learning identifies patterns predicts future rates. In India (2010-2024), Python's Pandas Scikit-learn used linear regression to forecast trends, showing annual increases. Residuals analysis confirms model accuracy, suggesting that strategies are effective room for improvement exists.

Language: Английский

Citations

0
Enhancing Moment Capacity Prediction in FRP-Reinforced Concrete Beams through Soft Computing Models DOI
Reza Andasht Kazeroon, Nima Ezami, Seyed Mohammad Khatami

et al.

Journal of structural design and construction practice., Journal Year: 2025, Volume and Issue: 30(2)

Published: Jan. 20, 2025

Language: Английский

Citations

0
Automated prediction of size-independent tensile strength and fracture toughness of concrete using machine learning techniques DOI
Tian Lan,

Shutong Yang,

Yufeng Jiang

et al.

Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 112431 - 112431

Published: March 1, 2025

Language: Английский

Citations

0
Machine learning assisted design of low-carbon aluminosilicate cementitious composites with diverse raw materials and target mechanical strength DOI Creative Commons
Jinyang Jiang, Yi Liu, Junlin Lin

et al.

Case Studies in Construction Materials, Journal Year: 2025, Volume and Issue: unknown, P. e04664 - e04664

Published: April 1, 2025

Language: Английский

Citations

0