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).

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Description/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.

Item Type: Conference or Workshop Item (Paper)
Digital Object Identifier (DOI): doi:10.1007/978-3-642-25566-3
Venue - Dates: Learning and Intelligent OptimizatioN (LION 5), Italy, 2011-05-25
Related URLs:
Subjects:
Organisations: Computational Engineering & Design Group
ePrint ID: 188459
Date :
Date Event
25 May 2011Published
Date Deposited: 25 May 2011 10:43
Last Modified: 18 Apr 2017 02:05
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/188459

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