CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

authors Wadhwa, Ashwan and Lonsway, Brian
year 2001
title A Self-Organizing Neural System for Urban Design
source Reinventing the Discourse - How Digital Tools Help Bridge and Transform Research, Education and Practice in Architecture [Proceedings of the Twenty First Annual Conference of the Association for Computer-Aided Design in Architecture / ISBN 1-880250-10-1] Buffalo (New York) 11-14 October 2001, pp. 386-391
summary The focus of this research is the development of an urban simulation system and its use to analyze growth factors in an urban design proposal. Unlike predictive simulation models, which attempt to accurately simulate future conditions resulting from a proposal, our neural network model is tuned to creatively present socioeconomic deficiencies and requirements for proposed developments. The system is built using a novel variant of Kohonenís self-organizing neural map algorithm. Urban data of a simulated region is embedded in the neural net and correlated, in varying degrees, with data obtained from case study and/or other local regions. By projecting design ideas onto this network, designers gain an insight into the proposalís impact based on complex, non-linear relationships of socio-economic data, which are otherwise difficult to envision.
keywords Neural Networks, Self Organizing Maps
series ACADIA
email wadhwa2@rpi.edu
full text file.pdf (96,906 bytes)
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