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国际不确定性的量化期刊

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ISSN 打印: 2152-5080

ISSN 在线: 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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ASSESSING THE PERFORMANCE OF LEJA AND CLENSHAW-CURTIS COLLOCATION FOR COMPUTATIONAL ELECTROMAGNETICS WITH RANDOM INPUT DATA

卷 9, 册 1, 2019, pp. 33-57
DOI: 10.1615/Int.J.UncertaintyQuantification.2018025234
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摘要

We consider the problem of quantifying uncertainty regarding the output of an electromagnetic field problem, in the presence of a large number of uncertain input parameters. In order to reduce the growth in complexity with the number of dimensions, we employ a dimension-adaptive stochastic collocation method based on nested univariate nodes. We examine the accuracy and performance of collocation schemes based on Clenshaw-Curtis and Leja rules, for the cases of uniform and bounded, nonuniform random inputs, respectively. Based on numerical experiments with an academic electromagnetic field model, we compare the two rules in both the univariate and multivariate cases and for both quadrature and interpolation purposes. Results for a real-world electromagnetic field application featuring high-dimensional input uncertainty are also presented.

对本文的引用
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  7. Galetzka Armin, Bontinck Zeger, Romer Ulrich, Schops Sebastian, A Multilevel Monte Carlo Method for High-Dimensional Uncertainty Quantification of Low-Frequency Electromagnetic Devices, IEEE Transactions on Magnetics, 55, 8, 2019. Crossref

  8. Li Kun, Huang Ting-Zhu, Li Liang, Zhao Ying, Lanteri Stéphane, A non-intrusive model order reduction approach for parameterized time-domain Maxwell's equations, Discrete and Continuous Dynamical Systems - B, 2022. Crossref

  9. Römer Ulrich, Bollhöfer Matthias, Sreekumar Harikrishnan, Blech Christopher, Christine Langer Sabine, An adaptive sparse grid rational Arnoldi method for uncertainty quantification of dynamical systems in the frequency domain, International Journal for Numerical Methods in Engineering, 122, 20, 2021. Crossref

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