Generative Adversarial Networks in the built environment: A comprehensive review of the application of GANs across data types and scales

AN Wu, R Stouffs, F Biljecki - Building and Environment, 2022 - Elsevier
Abstract Generative Adversarial Networks (GANs) are a type of deep neural network that
have achieved many state-of-the-art results for generative tasks. GANs can be useful in the …

A review on the current usage of machine learning tools for daylighting design and control

J Ngarambe, I Adilkhanova, B Uwiragiye… - Building and …, 2022 - Elsevier
Proper use of daylighting improves visual and thermal comfort in indoor environments and
minimizes dependency on artificial lighting, saving substantial amounts of energy …

Accelerated environmental performance-driven urban design with generative adversarial network

C Huang, G Zhang, J Yao, X Wang, JK Calautit… - Building and …, 2022 - Elsevier
The morphological design of urban blocks greatly affects the outdoor environment.
Currently, performance-based urban and building design relies on a time-consuming …

Optimization and prediction in the early design stage of office buildings using genetic and XGBoost algorithms

H Yan, K Yan, G Ji - Building and Environment, 2022 - Elsevier
Incorporating intelligent optimization algorithms in the early stages of office building design
facilitates a better response to the local climate. The indoor and outdoor thermal …

Machine learning in architecture

B Topuz, NÇ Alp - Automation in Construction, 2023 - Elsevier
This paper explores the utilisation of machine learning in architecture, focusing on the
addressed problems and commonly employed programming languages, software, platforms …

Automatic responsive-generation of 3D urban morphology coupled with local climate zones using generative adversarial network

S Zhou, Y Wang, W Jia, M Wang, Y Wu, R Qiao… - Building and …, 2023 - Elsevier
Decoupling the intricate relationship between three-dimensional (3D) urban morphology
and local climate is paramount importance in the realm of adaptive urban planning …

[HTML][HTML] Identifying influential architectural design variables for early-stage building sustainability optimization

X Wang, R Teigland, A Hollberg - Building and Environment, 2024 - Elsevier
Architectural design variables (ADVs) highly influence a building's sustainability
performance. Thus, identifying which ADVs are most influential in a building's early stages is …

A review and guide on selecting and optimizing machine learning algorithms for daylight prediction

Q Liu, Y Chen, Y Liu, Y Lei, Y Wang, P Hu - Building and Environment, 2023 - Elsevier
Daylight confers extensive benefits for building occupants and improves energy efficiency;
thus, its prediction and performance are significant for design decision-making on building …

An interactive assessment framework for residential space layouts using pix2pix predictive model at the early-stage building design

F Mostafavi, M Tahsildoost, ZS Zomorodian… - Smart and Sustainable …, 2024 - emerald.com
Purpose In this study, a novel framework based on deep learning models is presented to
assess energy and environmental performance of a given building space layout, facilitating …

A systematic review on artificial intelligence applications in architecture

B Bölek, O Tutal, H Özbaşaran - Journal of Design for Resilience in …, 2023 - drarch.org
Since the advent and usage of artificial intelligence approaches in architecture, a significant
number of studies have focused on integrating technological solutions to architectural …