Dealing with Inconsistent Measurements in Inverse Problems: An Approach Based on Sets and Intervals

We consider the (inverse) problem of finding back the parameter values of a physical model given a set of measurements. As the deterministic solution to this problem is sensitive to measurement error in the data, one way to resolve this issue is to take into account uncertainties in the data. In thi...

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Autores principales: Shinde, Krushna, Feissel, Pierre, Destercke, Sébastien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274699/
http://dx.doi.org/10.1007/978-3-030-50153-2_34
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author Shinde, Krushna
Feissel, Pierre
Destercke, Sébastien
author_facet Shinde, Krushna
Feissel, Pierre
Destercke, Sébastien
author_sort Shinde, Krushna
collection PubMed
description We consider the (inverse) problem of finding back the parameter values of a physical model given a set of measurements. As the deterministic solution to this problem is sensitive to measurement error in the data, one way to resolve this issue is to take into account uncertainties in the data. In this paper, we explore how interval-based approaches can be used to obtain a solution to the inverse problem, in particular when measurements are inconsistent with one another. We show on a set of experiments, in which we compare the set-based approach with the Bayesian one, that this is particularly interesting when some measurements can be suspected of being outliers.
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spelling pubmed-72746992020-06-08 Dealing with Inconsistent Measurements in Inverse Problems: An Approach Based on Sets and Intervals Shinde, Krushna Feissel, Pierre Destercke, Sébastien Information Processing and Management of Uncertainty in Knowledge-Based Systems Article We consider the (inverse) problem of finding back the parameter values of a physical model given a set of measurements. As the deterministic solution to this problem is sensitive to measurement error in the data, one way to resolve this issue is to take into account uncertainties in the data. In this paper, we explore how interval-based approaches can be used to obtain a solution to the inverse problem, in particular when measurements are inconsistent with one another. We show on a set of experiments, in which we compare the set-based approach with the Bayesian one, that this is particularly interesting when some measurements can be suspected of being outliers. 2020-05-16 /pmc/articles/PMC7274699/ http://dx.doi.org/10.1007/978-3-030-50153-2_34 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Shinde, Krushna
Feissel, Pierre
Destercke, Sébastien
Dealing with Inconsistent Measurements in Inverse Problems: An Approach Based on Sets and Intervals
title Dealing with Inconsistent Measurements in Inverse Problems: An Approach Based on Sets and Intervals
title_full Dealing with Inconsistent Measurements in Inverse Problems: An Approach Based on Sets and Intervals
title_fullStr Dealing with Inconsistent Measurements in Inverse Problems: An Approach Based on Sets and Intervals
title_full_unstemmed Dealing with Inconsistent Measurements in Inverse Problems: An Approach Based on Sets and Intervals
title_short Dealing with Inconsistent Measurements in Inverse Problems: An Approach Based on Sets and Intervals
title_sort dealing with inconsistent measurements in inverse problems: an approach based on sets and intervals
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274699/
http://dx.doi.org/10.1007/978-3-030-50153-2_34
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