Publication
Title
A novel sequential design strategy for global surrogate modeling
Author
Abstract
In mathematical/statistical modeling of complex systems, the locations of the data points are essential to the success of the algorithm. Sequential design methods are iterative algorithms that use data acquired from previous iterations to guide future sample selection. They are often used to improve an initial design such as a Latin hypercube or a simple grid, in order to focus on highly dynamic parts of the design space. In this paper, a comparison is made between different sequential design methods for global surrogate modeling on a real-world electronics problem. Existing exploitation and exploration-based methods are compared against a novel hybrid technique which incorporates both an exploitation criterion, using local linear approximations of the objective function, and an exploration criterion, using a Monte Carlo Voronoi tessellation. The test results indicate that a considerable improvement of the average model accuracy can be achieved by using this new approach.
Language
English
Source (book)
Proceedings of the Winter Simulation Conference, December 13-16, 2009, Austin, Texas
Publication
New York, N.Y. : IEEE, 2009
ISBN
978-1-4244-5770-0
Volume/pages
p. 693-704
ISI
000289492500067
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 22.06.2011
Last edited 25.03.2017
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