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SUMMARY:Bayesian Optimisation for Structures: Challenges and Recommendatio
 ns - Thomas Archbold\, University of Cambridge
DTSTART:20211029T140000Z
DTEND:20211029T150000Z
UID:TALK166624@talks.cam.ac.uk
CONTACT:Mishael Nuh
DESCRIPTION:Structural optimisation is an essential tool for reducing gree
 nhouse gas emissions from the building and transportation sectors. Many fi
 nite element models used for simulation are computationally expensive and 
 are called “black- box” because of their lack of derivative informatio
 n. This limits the applicability of many gradient-based methods. Bayesian 
 optimisation is a “data-driven” approach used to efficiently optimise 
 “black-box” objective functions that are computationally expensive to 
 evaluate. Structural optimisation problems can be high-dimensional and sca
 ling Bayesian optimisation to such settings remains a barrier to its wide-
 spread use in practice. This project aims to explore how Bayesian optimisa
 tion can be used to solve high- dimensional structural optimisation proble
 ms.
LOCATION:Zoom (email structures-admin@eng.cam.ac.uk for link)
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