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. In, Learning and Intelligent OptimizatioN (LION 5), Rome, IT, 4pp. (doi:10.1007/978-3-642-25566-3).
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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|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||University Structure - Pre August 2011 > School of Engineering Sciences > Computational Engineering and Design
Faculty of Engineering and the Environment > Aeronautics, Astronautics and Computational Engineering > Computational Engineering & Design
|Date Deposited:||25 May 2011 10:43|
|Last Modified:||31 Mar 2016 13:39|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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