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International Journal for Uncertainty Quantification

年間 6 号発行

ISSN 印刷: 2152-5080

ISSN オンライン: 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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A STUDY ON Z-SOFT ROUGH FUZZY SEMIGROUPS AND ITS DECISION-MAKING

巻 8, 発行 1, 2018, pp. 1-22
DOI: 10.1615/Int.J.UncertaintyQuantification.2017021012
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要約

The hybrid soft set model is an important topic dealing with uncertain information. In this article, we firstly introduce the concept of Z-soft rough fuzzy sets of a semigroup, and obtain some basic operations about the upper (lower) approximations. Next, we give the definition of Z-soft rough fuzzy semigroups and study related properties. Particularly, we form an approach which is built on the basis of Z-soft rough fuzzy sets of a semigroup for decision-making, and we also give an example to test the validity of the approach. Finally, we compare the performance of three algorithms for decision-making, stated in terms of hybrid soft set models, inclusive of our Z-soft rough fuzzy sets. We use computer simulations in a medical environment with Matlab programs that are provided in an Appendix.

によって引用された
  1. Zhang Li, Zhan Jianming, Alcantud José Carlos R., Novel classes of fuzzy soft $$\beta $$ β -coverings-based fuzzy rough sets with applications to multi-criteria fuzzy group decision making, Soft Computing, 23, 14, 2019. Crossref

  2. Kanwal Shazia, Azam Akbar, Bounded lattice fuzzy coincidence theorems with applications, Journal of Intelligent & Fuzzy Systems, 36, 2, 2019. Crossref

  3. Kanwal Shazia, Shagari Mohammed Shehu, Aydi Hassen, Mukheimer Aiman, Abdeljawad Thabet, Common fixed-point results of fuzzy mappings and applications on stochastic Volterra integral equations, Journal of Inequalities and Applications, 2022, 1, 2022. Crossref

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