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Towards an intelligent non-stationary performance prediction of engineering systems

Toal, David J.J. and Keane, A.J. (2011) Towards an intelligent non-stationary performance prediction of engineering systems At Learning and Intelligent OptimizatioN (LION 5), Italy. 4 pp. (doi:10.1007/978-3-642-25566-3).

Record type: Conference or Workshop Item (Paper)

Abstract

The analysis of complex engineering systems can often be expensive thereby necessitating the use of surrogate models within any design optimization. However, the time variant response of quantities of interest can be non-stationary in nature and therefore difficult to represent effectively with traditional surrogate modelling techniques. The following paper presents the application of partial non-stationary kriging to the prediction of time variant responses where the definition of the non-linear mapping scheme is based upon prior knowledge of either the inputs to, or the nature of, the engineering system considered.

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More information

Published date: 25 May 2011
Venue - Dates: Learning and Intelligent OptimizatioN (LION 5), Italy, 2011-05-25
Organisations: Computational Engineering & Design Group

Identifiers

Local EPrints ID: 188459
URI: http://eprints.soton.ac.uk/id/eprint/188459
PURE UUID: 3e4b644e-4209-4f32-aec7-2c1d1b9e4823
ORCID for David J.J. Toal: ORCID iD orcid.org/0000-0002-2203-0302

Catalogue record

Date deposited: 25 May 2011 10:43
Last modified: 18 Jul 2017 11:42

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