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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

TRAPEZOIDAL INTERVAL TYPE-2 FUZZY MACLAURIN SYMMETRIC MEAN OPERATORS AND THEIR APPLICATIONS TO MULTIPLE ATTRIBUTE GROUP DECISION MAKING

Volume 8, Numéro 4, 2018, pp. 343-360
DOI: 10.1615/Int.J.UncertaintyQuantification.2018020768
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RÉSUMÉ

More and more scholars are engaged in research on trapezoidal interval type-2 fuzzy sets, which are more capable of handling uncertain and imprecise information than type-1 fuzzy sets. The Maclaurin symmetric mean (MSM) operator can effectively capture and handle the interrelationships among multiple arguments. In this paper, we investigate multiple attribute group decision making (MAGDM) problems in which the decision attributes are interdependent and the attribute values take the forms of trapezoidal interval type-2 fuzzy numbers. Firstly, we extend the MSM operator to a trapezoidal interval type-2 fuzzy environment and propose some aggregation operators, such as the trapezoidal interval type-2 fuzzy Maclaurin symmetric mean operator (IT2FMSM) and the weighted trapezoidal interval type-2 fuzzy Maclaurin symmetric mean (WIT2FMSM) operator. Then, we investigate some desirable properties and discuss some special cases when the parameters in these operators take different values. Moreover, we develop a novel MAGDM approach based on the WIT2FMSM operator under a trapezoidal interval type-2 fuzzy environment. Finally, we provide a practical example about the evaluation of the medical services quality of hospitals to demonstrate the effectiveness and practicality of the presented method and give a comparative analysis of the presented method with existing methods.

CITÉ PAR
  1. Meng Fanyong, Li Shutian, Tang Jie, A new interval type-2 trapezoid fuzzy multi-attribute group decision-making method and its application to the evaluation of sponge city construction, Artificial Intelligence Review, 54, 6, 2021. Crossref

  2. Sun Le, Dong Hai, Liu Alex X., Aggregation Functions Considering Criteria Interrelationships in Fuzzy Multi-Criteria Decision Making: State-of-the-Art, IEEE Access, 6, 2018. Crossref

  3. Lu Keyu, Liao Huchang, A survey of group decision making methods in Healthcare Industry 4.0: bibliometrics, applications, and directions, Applied Intelligence, 2022. Crossref

  4. Tang Guolin, Chiclana Francisco, Lin XiangChun, Liu Peide, Interval type-2 fuzzy multi-attribute decision-making approaches for evaluating the service quality of Chinese commercial banks, Knowledge-Based Systems, 193, 2020. Crossref

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