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International Journal for Uncertainty Quantification

Publication de 6  numéros par an

ISSN Imprimer: 2152-5080

ISSN En ligne: 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

Indexed in

EMPIRICAL ACCELERATION FUNCTIONS AND FUZZY INFORMATION

Volume 6, Numéro 3, 2016, pp. 215-228
DOI: 10.1615/Int.J.UncertaintyQuantification.2016016285
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RÉSUMÉ

In accelerated life testing approaches lifetime data are obtained under various conditions which are considered more severe than the usual condition. Classical analysis techniques are based on obtained precise measurements, and used to model variation among the observations. In fact, data have two types of uncertainty: variation among the observations and fuzziness of the single observation. Analysis techniques, which do not consider fuzziness and are only based on precise lifetime observations, lead to pseudo results. The aim of this study was to examine the behavior of empirical acceleration functions using fuzzy lifetime data. Furthermore the results showed an increased fuzziness in the transformed lifetimes compared to the input data.

CITÉ PAR
  1. Shafiq Muhammad, Atif Muhammad, Viertl Reinhard, Beyond precision: accelerated life testing for fuzzy life time data, Soft Computing, 22, 22, 2018. Crossref

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