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Investigating Bayesian robust experimental design with principles of global sensitivity analysis

He, Fei and Yue, Hong and Brown, Martin (2010) Investigating Bayesian robust experimental design with principles of global sensitivity analysis. In: 9th International Symposium on Dynamics and Control of Process Systems (DYCOPS 2010), 2010-07-05 - 2010-07-07, Lueven.

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Abstract

The purpose of model-based experimental design is to maximise the information gathered for quantitative model identification. Instead of the commonly used optimal experimental design, robust experimental design aims to address parametric uncertainties in the design process. In this paper, the Bayesian robust experimental design is investigated, where both a Monte Carlo sampling strategy and local sensitivity evaluation at each sampling point are employed to achieve the robust solution. The link between global sensitivity analysis (GSA) and the Bayesian robust experimental design is established. It is revealed that a lattice sampling based GSA strategy, the Morris method, can be explicitly interpreted as the Bayesian A-optimal design for the uniform hypercube type uncertainties.

Item type: Conference or Workshop Item (Paper)
ID code: 35270
Keywords: bayesian analysis, global sensitivity analysis , modeling, Electrical engineering. Electronics Nuclear engineering
Subjects: Technology > Electrical engineering. Electronics Nuclear engineering
Department: Faculty of Engineering > Electronic and Electrical Engineering
Related URLs:
    Depositing user: Pure Administrator
    Date Deposited: 26 Oct 2011 16:45
    Last modified: 17 Jul 2013 16:18
    URI: http://strathprints.strath.ac.uk/id/eprint/35270

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