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Learning surrogate models for simulation‐based optimization

Published in AIChE Journal • Feb 19, 2014
NobleIDNI1P91W45R69S62
Authors:
Alison Cozad
,
Nikolaos V. Sahinidis
,
David C. Miller

Abstract

A central problem in modeling, namely that of learning an algebraic model from data obtained from simulations or experiments is addressed. A methodology that uses a small number of simulations or experiments to learn models that are as accurate and as simple as possible is proposed. The approach beg...

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