The Potential of AI in Information Provision in Energy-Efficient Renovations: A Narrative Review of Literature DOI Creative Commons
Cemal Koray Bingöl, Tong Wang, Aksel Ersoy

et al.

Urban Planning, Journal Year: 2024, Volume and Issue: 10

Published: Oct. 21, 2024

<p>Energy-efficient renovation (EER) is a complex process essential for reducing emissions in the built environment. This research identifies homeowners as main decision-makers, whereas intermediaries and social interactions between peers are highly influential home renovations. It investigates information communication barriers encountered during initial phases of EERs. The study reviews AI tools developed within EERs domain to assess their capabilities overcoming these areas needing improvement. examines stakeholders, barriers, literature discussion compares functionalities against stakeholder needs challenges they face. Findings show that often overlook methodologies human–computer interaction potential textual visual methods. Digital tool development also lacks insights from science user feedback, potentially limiting practical impact innovations. article contributes by proposing an AI-supported framework outlining future exploration, particularly improving effectiveness engagement scale up EER practice.</p>

Language: Английский

A high-speed numerical simulation method for diverse boundary conditions for real time applications unleashing MeshGraphNet DOI
Avishek Mukherjee, Surjya K. Pal, Debashish Chakravarty

et al.

Engineering Analysis with Boundary Elements, Journal Year: 2025, Volume and Issue: 175, P. 106204 - 106204

Published: March 11, 2025

Language: Английский

Citations

0

AI-driven optimisation of metal alloys for space applications DOI Creative Commons

L. J. Rickard,

Adamantios Bampoulas,

Meena Laad

et al.

Discover Artificial Intelligence, Journal Year: 2025, Volume and Issue: 5(1)

Published: April 12, 2025

Language: Английский

Citations

0

A novel social network search and LightGBM framework for accurate prediction of blast-induced peak particle velocity DOI
Tianxing Ma,

Cuigang Chen,

Liangxu Shen

et al.

Frontiers of Structural and Civil Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 24, 2025

Language: Английский

Citations

0

Computational modeling of the magnetic couplings in Quadruple Perovskite CaCu3Mn2Os2O12: Monte Carlo investigation DOI
Hajar El Ganich, Omar Ben Lenda,

Soukaina Saissi

et al.

Applied Physics A, Journal Year: 2025, Volume and Issue: 131(5)

Published: May 1, 2025

Language: Английский

Citations

0

How the interplay between innovation ecosystems and market contingency factors impacts startup innovation DOI
Arthur Marcon, José Luís Duarte Ribeiro, Yasmin Olteanu

et al.

Technology in Society, Journal Year: 2023, Volume and Issue: 76, P. 102424 - 102424

Published: Nov. 23, 2023

Language: Английский

Citations

10

Image-based 3D reconstruction and permeability modelling of rock using enhanced interpretable deep residual learning DOI
Shan Lin, Miao Dong,

Zenglong Liang

et al.

Engineering Analysis with Boundary Elements, Journal Year: 2024, Volume and Issue: 160, P. 187 - 200

Published: Jan. 9, 2024

Language: Английский

Citations

3

Integrated hybrid machine learning techniques and multiscale modeling towards evaluating the influence of nano-material on strength of concrete DOI
Prashant B. Pande,

Sagar W. Dhengare,

Jayant M. Raut

et al.

Multiscale and Multidisciplinary Modeling Experiments and Design, Journal Year: 2024, Volume and Issue: 8(1)

Published: Nov. 7, 2024

Language: Английский

Citations

3

Automatic identification of rock fractures based on deep learning DOI

Yaopeng Ji,

Shengyuan Song, Wen Zhang

et al.

Engineering Geology, Journal Year: 2024, Volume and Issue: unknown, P. 107874 - 107874

Published: Dec. 1, 2024

Language: Английский

Citations

3

Data-Driven Distance Education Course Design: Content Recommendation Based on Big Data DOI

Shu Min Wan,

Yuerong Zhang

Smart innovation, systems and technologies, Journal Year: 2025, Volume and Issue: unknown, P. 461 - 471

Published: Jan. 1, 2025

Language: Английский

Citations

0

Stochastic Multiscale Modeling for Thermal Conductivity in Polymeric Graphene-Enhanced Composites: A Study in Interpretable Machine Learning DOI
Bokai Liu, Pengju Liu, Weizhuo Lu

et al.

Mechanisms and machine science, Journal Year: 2025, Volume and Issue: unknown, P. 208 - 219

Published: Jan. 1, 2025

Language: Английский

Citations

0