Advanced methods for measurement uncertainty evaluation

Zakharov, I.; Botsiura, O.

Публікація:
Advanced methods for measurement uncertainty evaluation

dc.contributor.author	Zakharov, I.
dc.contributor.author	Botsiura, O.
dc.date.accessioned	2024-03-18T14:10:22Z
dc.date.available	2024-03-18T14:10:22Z
dc.date.issued	2022
dc.description.abstract	Disadvantages of the law of propagation of uncertainty underlying the implementation of the model approach in the GUM are analyzed. Advanced methods for implementing a model approach to measurement uncertainty evaluation are described, which allow eliminating the shortcomings of the GUM uncertainty framework: the law of propagation of distributions, the kurtosis method, the law of propagation of expanded uncertainty, the law of propagation of observational results for reliable evaluation of type A uncertainty for correlated and uncorrelated measurement results of input quantities.
dc.identifier.citation	Zakharov I. Advanced methods for measurement uncertainty evaluation / I. Zakharov, O. Botsiura // Metrology and Metrology Assurance (MMA-2022 ): Proceedings of 2022 XXXII International Scientific Symposium, Sozopol, Bulgaria, September 7-11, 2022. – Pp. 19-22.
dc.identifier.doi	https://doi.org/10.1109/MMA55579.2022.9993256
dc.identifier.uri	https://openarchive.nure.ua/handle/document/26104
dc.language.iso	en
dc.publisher	MMA-2022
dc.subject	model approach to measurement uncertainty evaluation
dc.subject	Monte Carlo method
dc.subject	kurtosis method
dc.subject	the law of propagation of expanded uncertainty
dc.subject	reduction method
dc.subject	transposition method
dc.title	Advanced methods for measurement uncertainty evaluation
dc.type	Conference proceedings
dspace.entity.type	Publication