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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

SOME INTERVAL NEUTROSOPHIC HESITANT UNCERTAIN LINGUISTIC BONFERRONI MEAN AGGREGATION OPERATORS FOR MULTIPLE ATTRIBUTE DECISION-MAKING

Volumen 7, Edición 6, 2017, pp. 525-572
DOI: 10.1615/Int.J.UncertaintyQuantification.2017020094
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SINOPSIS

Interval neutrosophic hesitant uncertain linguistic set (INHULS) has the advantages of both interval neutrosophic hesitant numbers and uncertain linguistic variables. In this paper, we firstly introduce the definition, the operational laws, and the score function of INHULS. Then, we combine the interval neutrosophic hesitant uncertain linguistic set with the Bonferroni mean operator and propose some new aggregation operators, such as the interval neutrosophic hesitant uncertain linguistic Bonferroni mean (INHULBM) operator, the interval neutrosophic hesitant uncertain linguistic weighted Bonferroni mean (INHULWBM) operator, the interval neutrosophic hesitant uncertain linguistic geometric Bonferroni mean (INHULGBM) operator, and the interval neutrosophic hesitant uncertain linguistic weighted geometric Bonferroni mean (INHULWGBM) operator. At the same time, the related properties of these operators are discussed. Furthermore, we propose two multiple attribute decision-making methods based on the INHULWBM operator and the INHULWGBM operator. Finally, we give an illustrative example to demonstrate the practicality and effectiveness of the proposed methods.

CITADO POR
  1. Liang Weizhang, Zhao Guoyan, Luo Suizhi, Selecting the Optimal Mine Ventilation System via a Decision Making Framework under Hesitant Linguistic Environment, Symmetry, 10, 7, 2018. Crossref

  2. Zhao Hu, Zhang Hong-Ying, On hesitant neutrosophic rough set over two universes and its application, Artificial Intelligence Review, 53, 6, 2020. Crossref

  3. Ahmad Zeeshan, Mahmood Tahir, Ullah Kifayat, Jan Naeem, Similarity Measures based on the Novel Interval-valued Picture Hesitant Fuzzy Sets and their Applications in Pattern Recognition, Punjab University Journal of Mathematics, 2022. Crossref

  4. Yang Zaoli, Zhang Tingting, Ahmad Salman, Gupta Shivam, A group decision‐making algorithm considering interaction and feedback mechanisms for dynamic supplier selection under q‐ rung orthopair fuzzy information , International Journal of Intelligent Systems, 37, 10, 2022. Crossref

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