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International Journal for Uncertainty Quantification
Главный редактор: Habib N. Najm (open in a new tab)
Ассоциированный редакторs: Dongbin Xiu (open in a new tab) Tao Zhou (open in a new tab)
Редактор-основатель: Nicholas Zabaras (open in a new tab)

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ISSN Печать: 2152-5080

ISSN Онлайн: 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 NOVEL MULTI-CRITERIA GROUP DECISION-MAKING APPROACH USING SIMPLIFIED NEUTROSOPHIC INFORMATION

Том 7, Выпуск 4, 2017, pp. 355-376
DOI: 10.1615/Int.J.UncertaintyQuantification.2017020126
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Краткое описание

This work develops a novel approach for multicriteria group decision-making (MCGDM) problems based on the Choquet integral with simplified neutrosophic information. In such an environment, the truth-membership, indeterminacy-membership, and falsity-membership degrees for each element are singleton subsets in [0, 1]. In this paper, considering the fact that the Einstein t-norms and t-conorms can manage the relation between the computed objectives, the Einstein operations of simplified neutrosophic numbers (SNNs) are defined. Then, three definitions for the distance of SNNs are presented. Subsequently, taking advantage of the Choquet integral and that it can reflect the correlation of objectives, two aggregation operators for SNNs are also defined: specifically, the simplified neutrosophic Choquet integral weighted averaging operator and the simplified neutrosophic Choquet integral weighted geometric operator. Also, the properties related to these two aggregation operators are discussed in detail. Additionally, based on the aggregation operators and the technique for order preference by similarity to ideal solution (TOPSIS), a novel approach is developed to resolve MCGDM problems based on SNNs and unknown weight information, which has not been extensively discussed in the existing literature. Finally, this work provides a practical example to illustrate the practicality and effectiveness of the proposed approach; a comparison analysis is also presented based on the same example.

ЦИТИРОВАНО В
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  12. Pamučar Dragan, Sremac Siniša, Stević Željko, Ćirović Goran, Tomić Dejan, New multi-criteria LNN WASPAS model for evaluating the work of advisors in the transport of hazardous goods, Neural Computing and Applications, 31, 9, 2019. Crossref

  13. Chou Jason Chih-sheng, Lin Yi-Fong, Lin Scott Shu-Cheng, A Further Study on Multiperiod Health Diagnostics Methodology under a Single-Valued Neutrosophic Set, Computational and Mathematical Methods in Medicine, 2020, 2020. Crossref

  14. Krishankumar R., Rani Pratibha, Ravichandran K. S., Aggarwal Manish, Peng Xindong, An integrated and discriminative approach for group decision-making with probabilistic linguistic information, Soft Computing, 25, 4, 2021. Crossref

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