Data-driven approximation algorithms for rapid performance evaluation and optimization of civil structures

Data-driven approximation algorithms for rapid performance evaluation and optimization of civil structures

This paper explores the use of data-driven approximation algorithms, often called surrogate modeling, in the early-stage design of structures. The use of surrogate models to rapidly evaluate design performance can lead to a more in-depth exploration of a design space and reduce computational time of...

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Bibliographic Details
Main Authors: Tseranidis, Stavros (Contributor), Brown, Nathan Collin (Contributor), Mueller, Caitlin T (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Architecture (Contributor), Massachusetts Institute of Technology. Computation for Design and Optimization Program (Contributor), Mueller, Caitlin T. (Contributor)
Format: Article
Language:English
Published: Elsevier, 2018-12-04T16:07:42Z.
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