Assessing Steady-State, Multivariate Experimental Data Using Gaussian Processes: The GPExp Open-Source Library

Sylvain Quoilin and Jessica Schrouff
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Sylvain Quoilin: Energy Systems Research Unit (B49), University of Liège, Sart-Tilman, Liège 4000, Belgium
Jessica Schrouff: Laboratory of Behavioral and Cognitive Neuroscience, Stanford University, 300 Pasteur Drive, Stanford, CA 94305, USA

Energies, 2016, vol. 9, issue 6, 1-16

Abstract: Experimental data are subject to different sources of disturbance and errors, whose importance should be assessed. The level of noise, the presence of outliers or a measure of the “explainability” of the key variables with respect to the externally-imposed operating condition are important indicators, but are not straightforward to obtain, especially if the data are sparse and multivariate. This paper proposes a methodology and a suite of tools implementing Gaussian processes for quality assessment of steady-state experimental data. The aim of the proposed tool is to: (1) provide a smooth (de-noised) multivariate operating map of the measured variable with respect to the inputs; (2) determine which inputs are relevant to predict a selected output; (3) provide a sensitivity analysis of the measured variables with respect to the inputs; (4) provide a measure of the accuracy (confidence intervals) for the prediction of the data; (5) detect the observations that are likely to be outliers. We show that Gaussian processes regression provides insightful numerical indicators for these purposes and that the obtained performance is higher or comparable to alternative modeling techniques. Finally, the datasets and tools developed in this work are provided within the GPExp open-source package.

Keywords: Gaussian processes; experimental data; outlier; surface response; kriging; regression; feature selection (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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