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Title: Clustering of architectural floor plans: A comparison of shape representations
Authors: Rodrigues, Eugénio 
Sousa-Rodrigues, David 
Teixeira de Sampayo, Mafalda 
Gaspar, Adélio Rodrigues 
Gomes, Álvaro 
Antunes, Carlos Henggeler 
Keywords: Unsupervised clustering; Floor plan designs; Hierarchical clustering; Shape representation; Descriptors
Issue Date: Aug-2017
Publisher: Elsevier
Project: Ren4EEnIEQ (PTDC/EMS-ENE/3238/2014, POCI-01-0145-FEDER-016760, LISBOA-01-0145-FEDER-016760) 
Serial title, monograph or event: Automation in Construction
Volume: 80
Abstract: Generative design methods are able to produce a large number of potential solutions of architectural floor plans, which may be overwhelming for the decision-maker to cope with. Therefore, it is important to develop tools which organise the generated data in a meaningful manner. In this study, a comparative analysis of four architectural shape representations for the task of unsupervised clustering is presented. Three of the four shape representations are the Point Distance, Turning Function, and Grid-Based model approaches, which are based on known descriptors. The fourth proposed representation, Tangent Distance, calculates the distances of the contour's tangents to the shape's geometric centre. A hierarchical agglomerative clustering algorithm is used to cluster a synthetic dataset of 72 floor plans. When compared to a reference clustering, despite good perceptual results with the use of the Point Distance and Turning Function representations, the Tangent Distance descriptor (Rand index of 0.873) provides the best results. The Grid-Based descriptor presents the worst results.
ISSN: 0926-5805
DOI: 10.1016/j.autcon.2017.03.017
Rights: openAccess
Appears in Collections:FCTUC Eng.Mecânica - Artigos em Revistas Internacionais

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