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...
Main Authors: | Tseranidis, Stavros, Brown, Nathan Collin, Mueller, Caitlin T |
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Other Authors: | Massachusetts Institute of Technology. Department of Architecture |
Format: | Article |
Language: | en_US |
Published: |
Elsevier
2018
|
Online Access: | http://hdl.handle.net/1721.1/119411 https://orcid.org/0000-0002-9554-8292 https://orcid.org/0000-0003-1538-9787 https://orcid.org/0000-0001-7646-8505 |
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