Machine learning in architecture

This paper explores the utilisation of machine learning in architecture, focusing on the addressed problems and commonly employed programming languages, software, platforms, libraries, and algorithms. Eight major academic search and publishing platforms were systematically reviewed, covering the per...

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Published inAutomation in construction Vol. 154; p. 105012
Main Authors Topuz, Beyza, Çakici Alp, Neşe
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.10.2023
Subjects
Machine learning algorithms
Machine learning in architecture
Machine learning libraries
Machine learning platforms
Systematic review
Machine learning in architecture
Machine learning platforms
Systematic review
Machine learning libraries
Machine learning algorithms
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Abstract This paper explores the utilisation of machine learning in architecture, focusing on the addressed problems and commonly employed programming languages, software, platforms, libraries, and algorithms. Eight major academic search and publishing platforms were systematically reviewed, covering the period from 2007 to 2022, resulting in the selection of 60 relevant articles from a pool of 175. The articles were categorised based on their thematic focus, primarily centring around Computer-Aided Design (CAD), Computer-Aided Engineering (CAE), and Computer-Aided Manufacturing (CAM). By evaluating the current state of machine learning in architecture, this study provides valuable insights into its usage and identifies potential areas for future research. This paper contributes to a comprehensive understanding of the evolving landscape of machine learning in the field by investigating subfields within architecture and the specific tools used to tackle architectural challenges. •Conducting a systematic review to investigate the application of machine learning in architecture.•Examining the subfields of architecture that have been studied through machine learning and the problems addressed within them.•Analysing the utilisation of programming languages, software, machine learning platforms, programming libraries, and machine learning algorithms in architecture.•Focusing on published works between 2007 and 2022 that utilize machine learning in the field of architecture.
AbstractList This paper explores the utilisation of machine learning in architecture, focusing on the addressed problems and commonly employed programming languages, software, platforms, libraries, and algorithms. Eight major academic search and publishing platforms were systematically reviewed, covering the period from 2007 to 2022, resulting in the selection of 60 relevant articles from a pool of 175. The articles were categorised based on their thematic focus, primarily centring around Computer-Aided Design (CAD), Computer-Aided Engineering (CAE), and Computer-Aided Manufacturing (CAM). By evaluating the current state of machine learning in architecture, this study provides valuable insights into its usage and identifies potential areas for future research. This paper contributes to a comprehensive understanding of the evolving landscape of machine learning in the field by investigating subfields within architecture and the specific tools used to tackle architectural challenges. •Conducting a systematic review to investigate the application of machine learning in architecture.•Examining the subfields of architecture that have been studied through machine learning and the problems addressed within them.•Analysing the utilisation of programming languages, software, machine learning platforms, programming libraries, and machine learning algorithms in architecture.•Focusing on published works between 2007 and 2022 that utilize machine learning in the field of architecture.
ArticleNumber 105012
Author Çakici Alp, Neşe
Topuz, Beyza
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crossref_primary_10_1016_j_autcon_2023_105187
crossref_primary_10_3390_buildings14010108
crossref_primary_10_3390_math12020295
crossref_primary_10_1007_s43503_024_00022_w
crossref_primary_10_1016_j_undsp_2023_11_008
crossref_primary_10_3390_bioengineering11070671
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Machine learning platforms
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SubjectTerms Machine learning algorithms
Machine learning in architecture
Machine learning libraries
Machine learning platforms
Systematic review
Title Machine learning in architecture
URI https://dx.doi.org/10.1016/j.autcon.2023.105012
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