Design Space Exploration and Explanation via Conditional Variational Autoencoders in Meta-Model-Based Conceptual Design of Pedestrian Bridges

Today, engineers rely on conventional iterative (often manual) techniques for conceptual design. Emerging parametric models facilitate design space exploration based on quantifiable performance metrics, yet remain time-consuming and computationally expensive, leaving room for improvement. This paper...

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Bibliographic Details

Published in:	Automation in construction Vol. 163; p. 105411
Main Authors:	Balmer, Vera, Kuhn, Sophia V., Bischof, Rafael, Salamanca, Luis, Kaufmann, Walter, Perez-Cruz, Fernando, Kraus, Michael A.
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.07.2024
Subjects:	Computational design Conditional Variational Autoencoder Design space exploration Explainable AI Generative AI Pedestrian bridge Generative AI Explainable AI Pedestrian bridge Conditional Variational Autoencoder Design space exploration Computational design
ISSN:	0926-5805, 1872-7891
Online Access:	Get full text
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