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Structural Plan Schema Generation Through Generative Adversarial Networks
Öztürk Kösenciğ,Kamile Okuyucu,Elif Bahar Balaban,Özgün
Öztürk Kösenciğ,Kamile
Okuyucu,Elif Bahar
Balaban,Özgün
Abstract
This paper suggests a workfow that generates foor plans with structural elements. Generating structural layouts in a BIM environment with the implementation of a machine learning method allows a future projection for fast and easy exploration of multiple design options. Pix2Pix, a Generative Adversarial Networks (GAN) model, takes the wall layout as input and generates a structural layout by learning from existing knowledge used to generate a decision support system for structural layout generation. The paper also suggest an additional script as a fne-adjustment model to refne the structural layout based on predetermined structural rules. This script increases the accuracy of the structural layouts generated by the GAN algorithm. Based on the test dataset, the research demonstrates a 64% success rate in providing structural schema assistance. Considering the results, this study seems to have the potential to be a supportive application in the early design phase.
Description
Publisher Copyright: © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.
Date
2024-06
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Volume Title
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Research Projects
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Keywords
Artifcial intelligence (AI), GAN, Plan generator, Structural schema, Early design phase
Citation
Öztürk Kösenciğ, K, Okuyucu, E B & Balaban, Ö 2024, 'Structural Plan Schema Generation Through Generative Adversarial Networks', Nexus Network Journal, vol. 26, no. 2, pp. 409-427. https://doi.org/10.1007/s00004-024-00766-z