Ranking of incomplete trapezoidal information
Any information system or decision model which consists of combinations of quantitative, qualitative, imprecise and incomplete informations can be modelled better using trapezoidal intuitionistic fuzzy numbers (TrIFNs) than interval valued intuitionistic fuzzy numbers. Ranking of TrIFNs plays an imp...
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Veröffentlicht in: | Soft computing (Berlin, Germany) Germany), 2017-12, Vol.21 (23), p.7125-7140 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Any information system or decision model which consists of combinations of quantitative, qualitative, imprecise and incomplete informations can be modelled better using trapezoidal intuitionistic fuzzy numbers (TrIFNs) than interval valued intuitionistic fuzzy numbers. Ranking of TrIFNs plays an important role in intuitionistic fuzzy decision-making or intuitionistic fuzzy information system. In this paper, a new method for ranking of TrIFNs using membership, non-membership, vague and precise score functions which generalises the membership, non-membership, vague and precise score functions defined in Geetha et al. (Expert Syst Appl 41:1947–1954,
2014
) is proposed and a new algorithm for solving information system problem with incomplete information is introduced. Further, the significance of our proposed method over the existing methods is studied by an illustrative example. |
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ISSN: | 1432-7643 1433-7479 |
DOI: | 10.1007/s00500-016-2256-1 |