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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

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A NOVEL HYBRID APPROACH FOR SIMPLIFIED NEUTROSOPHIC DECISION-MAKING WITH COMPLETELY UNKNOWN WEIGHT INFORMATION

Volume 8, Numéro 2, 2018, pp. 161-173
DOI: 10.1615/Int.J.UncertaintyQuantification.2018021164
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RÉSUMÉ

The simplified neutrosophic set (SNS) is a useful model to describe the indeterminacy information which widely exists in the real world. In this paper, we develop a multicriteria decision-making (MCDM) method under simplified neutrosophic environment in which the information about weights of criteria is completely unknown, and the decision criterion values take the form of simplified neutrosophic numbers (SNNs). In order to determine the weighting vector of the criteria, we establish an optimization model based on the basic ideal of the traditional gray relational analysis (GRA) method. By solving this model, we get a simple and exact formula which can be used to determine the criterion weights. Moreover, we utilize the dice similarity measure to determine the similarity measures between each alternative decision and the related ideal decisions. Then, based on the traditional GRA method and the technique for order preference by similarity to ideal solution (TOPSIS), some calculation steps are presented for solving a simplified neutrosophic multicriteria decision-making problem with completely unknown weight information. To avoid information loss, this model does not use the aggregation process of decision information. Comparisons of the suggested methodology with other methods are also made. Finally, a numerical example and an experimental analysis are proposed to illustrate the application of the proposed model.

CITÉ PAR
  1. Xiong Wentao, Cheng Jing, A Novel Method for Determining the Attribute Weights in the Multiple Attribute Decision-Making with Neutrosophic Information through Maximizing the Generalized Single-Valued Neutrosophic Deviation, Information, 9, 6, 2018. Crossref

  2. KÜÇÜK Gökçe Dilek, Distance-Based Similarity Measure Between Interval Neutrosophic Sets and Multi Criteria Decision Making Method, Journal of the Institute of Science and Technology, 2019. Crossref

  3. Altun Fatma, Şahin Rıdvan, Güler Coşkun, Multi-criteria decision making approach based on PROMETHEE with probabilistic simplified neutrosophic sets, Soft Computing, 24, 7, 2020. Crossref

  4. 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

  5. Zhang Haibo, Mu Zhimin, Zeng Shouzhen, Multiple Attribute Group Decision Making Based on Simplified Neutrosophic Integrated Weighted Distance Measure and Entropy Method, Mathematical Problems in Engineering, 2020, 2020. Crossref

  6. Kou Yaqing, Feng Xue, Wang Jun, A Novel q-Rung Dual Hesitant Fuzzy Multi-Attribute Decision-Making Method Based on Entropy Weights, Entropy, 23, 10, 2021. Crossref

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