Sensitivity Analysis in Metrology: Study and Comparison on Different Indices for Measurement Uncertainty

Allard, Alexandre; Fischer, Nicolas

doi:10.1142/9789812839527_0001

Cited by 8 publications

(16 citation statements)

References 1 publication

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“…While derivatives can still play a role in global sensitivity analyses, other mathematical measures have been developed [5,6]. Some measures require independent inputs and/or the function to be linear.…”

Section: Terminologymentioning

confidence: 99%

“…In variance decomposition settings, the adjective total has been used to describe global sensitivity measures that account for all interaction effects, while the adjective firstorder has been used for measures that do not account for any such interactions [5]. The term one-at-a-time has been used to describe a sensitivity measure that fixes all inputs but one to their expected values [6]. Thus, one-at-a-time measures are neither completely local nor entirely global.…”

Section: Terminologymentioning

confidence: 99%

“…The GUM-S1 methodology involves constructing an empirical output distribution for the measurand by repeated numerical evaluation of the measurement function at samples drawn from the joint distribution of the inputs. Thus, the GUM-S1 finds particular use when the linearization of the measurement function is inadequate for application of the GUM, the computational cost of evaluating the measurement function is not prohibitive and the joint distribution of the inputs can numerically be sampled; see [3, section 5.4.3] and [10,[15][16][17] 6 .…”

Section: The Gum Frameworkmentioning

confidence: 99%

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Variance gradients and uncertainty budgets for nonlinear measurement functions with independent inputs

Campanelli

Kacker²,

Kessel³

2013

Meas. Sci. Technol.

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A novel variance-based measure for global sensitivity analysis, termed a variance gradient (VG), is presented for constructing uncertainty budgets under the Guide to the Expression of Uncertainty in Measurement (GUM) framework for nonlinear measurement functions with independent inputs. The motivation behind VGs is the desire of metrologists to understand which inputs' variance reductions would most effectively reduce the variance of the measurand. VGs are particularly useful when the application of the first supplement to the GUM is indicated because of the inadequacy of measurement function linearization. However, VGs reduce to a commonly understood variance decomposition in the case of a linear(ized) measurement function with independent inputs for which the original GUM readily applies. The usefulness of VGs is illustrated by application to an example from the first supplement to the GUM, as well as to the benchmark Ishigami function. A comparison of VGs to other available sensitivity measures is made.

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Section: Terminologymentioning

confidence: 99%

Section: Terminologymentioning

confidence: 99%

Section: The Gum Frameworkmentioning

confidence: 99%

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Variance gradients and uncertainty budgets for nonlinear measurement functions with independent inputs

Campanelli

Kacker²,

Kessel³

2013

Meas. Sci. Technol.

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“…In analytical propagation approach, the sensitivity coefficient may also be defined by Sobol's approach [10]. This method [11] is a variance based global sensitivity analysis technique founded upon "Total Sensitivity Indices" that account for interaction effects of the variables.…”

Section: Sobol's Methodmentioning

confidence: 99%

Simulation Method to Estimate the Uncertainties of Iso Specifications

Linares

Sprauel

2015

Series on Advances in Mathematics for Applied Sciences

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Copyright

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“…Once the data is quantitative, various methods can be applied in order to rank valid factors for any decisions. Methods can be statistical such as Variance Based Factor Prioritization [2] or subjective such as Analytical Hierarchy Process [3].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy cognitive mapping in factor elimination: A case study for innovative power and risks

Altay

Kayakutlu

2011

Procedia Computer Science

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Factor or criteria prioritization is essential for decision making and planning. In most areas in decision making, integrating the related literature yields an exuberance of criteria which leads a robust decision. Yet, an excess number of criteria may handicap decision making or evaluations in terms of computational time and complexity. In these circumstances, decreasing the number of factors in exchange for a negligible amount of knowledge can emancipate the decision maker yet does not affect the quality of the decision. This elimination can be conducted through qualitative methods such as interviews or quantitative methods. However, quantitative methods are more trustworthy since qualitative methods can be deceptive due to the perceptions of the interviewee. Furthermore, working with larger groups is more prone to neutrality in terms of group thinking. On the subject of innovative power and risks, the literature offers 48 criteria depending on the industry, size or demographics of related companies. Prioritizing and working with these criteria for their decision making applications becomes computationally expensive, especially when embedded in more complex algorithms. In this study, 48 criteria will be reduced using Fuzzy Cognitive Maps and it is believed to provide a sufficient number of criteria with a negligible loss of information and comparisons will be conducted.

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Sensitivity Analysis in Metrology: Study and Comparison on Different Indices for Measurement Uncertainty

Cited by 8 publications

References 1 publication

Variance gradients and uncertainty budgets for nonlinear measurement functions with independent inputs

Variance gradients and uncertainty budgets for nonlinear measurement functions with independent inputs

Simulation Method to Estimate the Uncertainties of Iso Specifications

Fuzzy cognitive mapping in factor elimination: A case study for innovative power and risks

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