DEEP WINNING FORM: Machine investigation of architectural quality

Frederick Chando Kim, Hong Bin Yang, Mikhael Johanes, Jeffrey Huang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper showcases the development of Arch-Form, a plat form that enables the investigation of underutilization of knowledge from architectural competitions, specifically within the Swiss architecture system. The aim is to leverage machine learning to analyse and understand architectural forms from school competition data spanning the past 20 years. The original contribution of this study lies in transforming competition results into a machine-learnable format, using 622 massing models to create 'architectural' point clouds. This methodology involves using 3D Adversarial Auto encoders (3dAAE) to encode and reconstruct these point clouds, experimenting with various structured formats such as uniform, horizontal and vertical g-codes. The main conclusion drawn is that machine learning can significantly aid in understanding and predicting architectural form preferences, documenting trends, and transformations in design. This approach enhances the computability of architectural forms. It offers a new perspective on how machines interpret and generate architectural data, contributing to a more comprehensive understanding of architectural evolution and societal preferences in design.

Original languageEnglish
Title of host publicationAccelerated Design - 29th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2024
EditorsNicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan
PublisherThe Association for Computer-Aided Architectural Design Research in Asia
Pages273-282
Number of pages10
ISBN (Print)9789887891826
Publication statusPublished - 2024
Event29th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2024 - Singapore, Singapore
Duration: 20 Apr 202426 Apr 2024

Publication series

NameProceedings of the International Conference on Computer-Aided Architectural Design Research in Asia
Volume2
ISSN (Print)2710-4257
ISSN (Electronic)2710-4265

Conference

Conference29th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2024
Country/TerritorySingapore
CitySingapore
Period20/04/2426/04/24

Keywords

  • Architectural Form
  • Architecture Competition
  • Digital Representation
  • Machine Learning
  • Point Clouds

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