Interval neutrosophic hesitant fuzzy Einstein Choquet integral operator for multicriteria decision making
Artificial Intelligence Review, ISSN: 1573-7462, Vol: 53, Issue: 3, Page: 2171-2206
2020
- 10Citations
- 12Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
Recently interval neutrosophic hesitant fuzzy sets are found to be more general and useful to express incomplete, indeterminate and inconsistent information. In this paper, we define some new Einstein operational rules on interval neutrosophic hesitant fuzzy elements, then we propose the interval neutrosophic hesitant fuzzy Einstein Choquet integral (INHFECI) operator and discuss its properties. Further, an approach for multicriteria decision making is developed to study the interaction between the input arguments under the interval neutrosophic hesitant fuzzy environment. The main advantage of the proposed operator is that, it can deal with the situations of the positive interaction, negative interaction or non-interaction among the criteria, during the decision making process. Also, the proposed operator can replace the weighted average to aggregate dependent criteria of interval neutrosophic hesistant fuzzy information for obtaining more accurate results. Moreover, some interval neutrosophic hesitant fuzzy weighted average operators are proposed as special cases of INHFECI operator. Finally, an illustrative example follows.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85068123039&origin=inward; http://dx.doi.org/10.1007/s10462-019-09730-7; http://link.springer.com/10.1007/s10462-019-09730-7; http://link.springer.com/content/pdf/10.1007/s10462-019-09730-7.pdf; http://link.springer.com/article/10.1007/s10462-019-09730-7/fulltext.html; https://dx.doi.org/10.1007/s10462-019-09730-7; https://link.springer.com/article/10.1007/s10462-019-09730-7
Springer Science and Business Media LLC
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