Associative spatial networks in architectural design: Artificial cognition of space using neural networks with spectral graph theory

John Harding, Christian Derix

Research output: Chapter or section in a book/report/conference proceedingBook chapter

5 Citations (SciVal)

Abstract

This paper looks at a new way of incorporating unsupervised neural networks in the design of an architectural system. The approach involves looking the whole lifecycle of a building and its coupling with its environment. It is argued that techniques such as dimensionality reduction are well suited to architectural design problems whereby complex problems are commonplace. An example project is explored, that of a reconfigurable exhibition space where multiple ephemeral exhibitions are housed at any given time. A modified growing neural gas algorithm is employed in order cognize similarities of dynamic spatial arrangements whose nature are not known a priori. By utilising the machine in combination with user feedback, a coupling between the building system and the users of the space is achieved throughout the whole system life cycle.
Original languageEnglish
Title of host publicationDesign Computing and Cognition '10
Place of PublicationDordrecht
PublisherSpringer
Pages305-323
Number of pages19
ISBN (Electronic)978-94-007-0510-4
ISBN (Print)978-94-007-0509-8
DOIs
Publication statusPublished - 2011
Event4th International Conference on Design Computing and Cognition, DCC'10, July 12, 2010 - July 14, 2010 - Stuttgart, Germany
Duration: 1 Jan 2011 → …

Publication series

NameDesign Computing and Cognition '10
PublisherSpringer Science and Business Media

Conference

Conference4th International Conference on Design Computing and Cognition, DCC'10, July 12, 2010 - July 14, 2010
Country/TerritoryGermany
CityStuttgart
Period1/01/11 → …

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