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id ijac20076104
authors Benoudjit, Mohamed Amine; Coates, Paul S.
year 2008
title Artificial networks for spatial analysis
source International Journal of Architectural Computing vol. 6 - no. 1, pp. 59-78
summary This paper tests digital representation techniques which can be used by artificial neural networks in a computer-aided design (CAD) environment to analyze and classify architectural spaces. We developed two techniques for encoding volumetric data: vertex representation and feature space representation, as input for artificial neural networks. We tested how two different kinds of artificial neural networks, perceptron networks and self-organizing maps, could recognize given shapes in these representational formats. We have found that a one-layer perceptron can be used to classify shapes even when presented with input vectors composed of real numbers. These spatial representation techniques provide a method for using ANNs for architectural purposes.
series journal
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last changed 2008/06/18 06:12
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