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International Journal for Uncertainty Quantification

Publicado 6 números por año

ISSN Imprimir: 2152-5080

ISSN En Línea: 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

INTERVAL-VALUED INTUITIONISTIC FUZZY POWER MACLAURIN SYMMETRIC MEAN AGGREGATION OPERATORS AND THEIR APPLICATION TO MULTIPLE ATTRIBUTE GROUP DECISION-MAKING

Volumen 8, Edición 3, 2018, pp. 211-232
DOI: 10.1615/Int.J.UncertaintyQuantification.2018020702
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SINOPSIS

The power average operator (PA), originally introduced by Yager (IEEE Trans. Syst. Man Cybern. Part A, 31(6):724–731, 2001), can reduce the negative impact of unreasonable evaluation values on the decision result. The Maclaurin symmetric mean (MSM), originally introduced by Maclaurin (Phil. Trans., 36:59–96, 1729), can reflect the interrelationship among the multi-input arguments. However, in some complex decision-making situations, we need to reduce the influence of unreasonable evaluation values and reflect the interrelationship among the multi-input arguments at the same time. In this paper, in order to solve such situations, we combine the ordinary PA operator with the traditional MSM in interval-valued intuitionistic context and propose two novel interval-valued intuitionistic fuzzy aggregation operators, i.e., the interval-valued intuitionistic fuzzy power Maclaurin symmetric mean operator and the weighted interval-valued intuitionistic fuzzy power Maclaurin symmetric mean operator. Then, some desirable properties of these new proposed operators are investigated and some special cases are discussed. Furthermore, based on these proposed operators, we develop a new approach to multiple attribute group decision-making under interval-valued intuitionistic fuzzy environment. Finally, two examples are provided to illustrate the feasibility and validity of the proposed approach by comparing to other existing representative methods.

CITADO POR
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