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International Journal for Uncertainty Quantification
Главный редактор: Habib N. Najm (open in a new tab)
Ассоциированный редакторs: Dongbin Xiu (open in a new tab) Tao Zhou (open in a new tab)
Редактор-основатель: Nicholas Zabaras (open in a new tab)

Выходит 6 номеров в год

ISSN Печать: 2152-5080

ISSN Онлайн: 2152-5099

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.7 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.9 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.5 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.0007 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.5 SJR: 0.584 SNIP: 0.676 CiteScore™:: 3 H-Index: 25

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FORWARD AND BACKWARD UNCERTAINTY PROPAGATION FOR DISCONTINUOUS SYSTEM RESPONSE USING THE PADÉ-LEGENDRE METHOD

Том 2, Выпуск 2, 2012, pp. 125-143
DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i2.40
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Краткое описание

The Pade-Legendre method has been introduced as an effective approach to characterize uncertainties in the presence of strongly non-linear or discontinuous system responsesthus, it supports forward propagation. The method is based on the construction of a ratio of polynomials that approximate the available data. Two criteria for the choice of the best approximant are considered and an optimization approach is proposed. Moreover, the approach is applied in a case in which the discontinuity in the system response is due to limited data, to demonstrate how the successive addition of data transforms the rational approximant into a simple polynomial interpolant (the denominator becomes a constant). Finally, the present method is applied to estimate an input parameter characterized by a sharp discontinuity, using Bayesian inference starting from observations of the system responsethus, it also supports backward propagation.

ЦИТИРОВАНО В
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