FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4284898982> ?p ?o ?g. }

• W4284898982 endingPage "34" @default.
• W4284898982 startingPage "1" @default.
• W4284898982 abstract "The coronavirus (COVID-19) pandemic, which began in China and is fast spreading around the world, has increased the number of cases and deaths. Governments have suffered substantial damage and losses not only in the health sector but also in a variety of other areas. In this situation, it is critical to determine the most crucial vaccine that doctors and specialists should implement. In order to evaluate the many vaccines to control the COVID-19 epidemic, a decision problem based on the decisions of many experts, with some contradicting and multiple criteria, should be taken into account. This decision process is characterized as a multiattribute group decision-making (MAGDM) problem that includes uncertainty in this study. <math xmlns=http://www.w3.org/1998/Math/MathML id=M2> <mi>T</mi> </math> -spherical fuzzy sets are utilized for this, allowing decision-experts to make evaluations over a larger area and better deal with complicated data. The <math xmlns=http://www.w3.org/1998/Math/MathML id=M3> <mi>T</mi> </math> -spherical fuzzy set is a useful tool for dealing with uncertainty and ambiguity, especially where additional answers of the type “yes,” “no,” “abstain,” and “refusal” are required, and the 2-tuple linguistic terms are useful for the qualitative evaluation of uncertain data. From the perspective of the uncertainty surrounding the problems of MAGDM, we propose the notion of 2-tuple linguistic <math xmlns=http://www.w3.org/1998/Math/MathML id=M4> <mi>T</mi> </math> -spherical fuzzy numbers (2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M5> <mi>T</mi> </math> -SFNs) generated with the integration of <math xmlns=http://www.w3.org/1998/Math/MathML id=M6> <mi>T</mi> </math> -spherical fuzzy numbers and 2-tuple linguistic terms. Then, the assessment based on distance from average solution (EDAS) for the ranking of alternatives based on the 2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M7> <mi>T</mi> </math> -SFNs is investigated as a new decision-making strategy. This study provides the following significant contributions: (1) the procedure for constructing a 2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M8> <mi>T</mi> </math> -SFNs is described, together with their aggregation operators, ranking criteria, relevant attributes, and some operational laws. (2) The traditional Maclaurin symmetric mean (MSM) operator is useful for modeling attribute interrelationships and aggregating 2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M9> <mi>T</mi> </math> -SF information to tackle the MAGDM problems. A few recent MSM and dual MSM operators are being built to evaluate the 2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M10> <mi>T</mi> </math> -SF information. Thus, 2-tuple linguistic <math xmlns=http://www.w3.org/1998/Math/MathML id=M11> <mi>T</mi> </math> -spherical fuzzy Maclaurin symmetric mean (2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M12> <mi>T</mi> </math> -SFMSM) operator, 2-tuple linguistic <math xmlns=http://www.w3.org/1998/Math/MathML id=M13> <mi>T</mi> </math> -spherical fuzzy weighted Maclaurin symmetric mean (2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M14> <mi>T</mi> </math> -SFWMSM) operator, 2-tuple linguistic <math xmlns=http://www.w3.org/1998/Math/MathML id=M15> <mi>T</mi> </math> -spherical fuzzy dual Maclaurin symmetric mean (2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M16> <mi>T</mi> </math> -SFDMSM) operator, and 2-tuple linguistic <math xmlns=http://www.w3.org/1998/Math/MathML id=M17> <mi>T</mi> </math> -spherical fuzzy weighted dual Maclaurin symmetric mean (2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M18> <mi>T</mi> </math> -SFWDMSM) operator are proposed. (3) We incorporate the 2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M19> <mi>T</mi> </math> -SFNs into the EDAS approach and develop a new 2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M20> <mi>T</mi> </math> -SF-EDAS method for solving the MAGDM problems based on the proposed aggregation operators in a 2TL <math xmlns=http://www.w3.org/1998/Math/MathML id=M21> <mi>T</mi> </math> -SF environment. A case study for the selection of an optimal vaccine to control the outbreak of the COVID-19 epidemic is also presented to show the validity of the proposed methodology. Furthermore, the comparative analysis with existing approaches shows the advantages and superiority of the proposed framework." @default.
• W4284898982 created "2022-07-09" @default.
• W4284898982 creator A5001270995 @default.
• W4284898982 creator A5028422756 @default.
• W4284898982 creator A5035644463 @default.
• W4284898982 creator A5051779439 @default.
• W4284898982 date "2022-07-07" @default.
• W4284898982 modified "2023-10-03" @default.
• W4284898982 title "Modified EDAS Method for MAGDM Based on MSM Operators with 2-Tuple Linguistic <math xmlns=http://www.w3.org/1998/Math/MathML id=M1> <mi>T</mi> </math>-Spherical Fuzzy Sets" @default.
• W4284898982 cites W1137073519 @default.
• W4284898982 cites W2003194756 @default.
• W4284898982 cites W2041210202 @default.
• W4284898982 cites W2259660946 @default.
• W4284898982 cites W2302915988 @default.
• W4284898982 cites W2311142332 @default.
• W4284898982 cites W2760060342 @default.
• W4284898982 cites W2804105936 @default.
• W4284898982 cites W2899072869 @default.
• W4284898982 cites W2903466805 @default.
• W4284898982 cites W2912368829 @default.
• W4284898982 cites W2951964871 @default.
• W4284898982 cites W2968470723 @default.
• W4284898982 cites W2986410383 @default.
• W4284898982 cites W2988030509 @default.
• W4284898982 cites W2995980274 @default.
• W4284898982 cites W3007428948 @default.
• W4284898982 cites W3010060064 @default.
• W4284898982 cites W3013493073 @default.
• W4284898982 cites W3036025030 @default.
• W4284898982 cites W3048680680 @default.
• W4284898982 cites W3083248186 @default.
• W4284898982 cites W3094106034 @default.
• W4284898982 cites W3094812779 @default.
• W4284898982 cites W3095324896 @default.
• W4284898982 cites W3095858262 @default.
• W4284898982 cites W3096734077 @default.
• W4284898982 cites W3102403735 @default.
• W4284898982 cites W3103686699 @default.
• W4284898982 cites W3111931909 @default.
• W4284898982 cites W3112496223 @default.
• W4284898982 cites W3112548563 @default.
• W4284898982 cites W3113924469 @default.
• W4284898982 cites W3115959878 @default.
• W4284898982 cites W3119433310 @default.
• W4284898982 cites W3120291472 @default.
• W4284898982 cites W3121700030 @default.
• W4284898982 cites W3121924295 @default.
• W4284898982 cites W3122489303 @default.
• W4284898982 cites W3122730067 @default.
• W4284898982 cites W3127348178 @default.
• W4284898982 cites W3129325581 @default.
• W4284898982 cites W3130470165 @default.
• W4284898982 cites W3134206376 @default.
• W4284898982 cites W3134627904 @default.
• W4284898982 cites W3150208416 @default.
• W4284898982 cites W3154834574 @default.
• W4284898982 cites W3155296129 @default.
• W4284898982 cites W3155792888 @default.
• W4284898982 cites W3161014367 @default.
• W4284898982 cites W3162293853 @default.
• W4284898982 cites W3163070442 @default.
• W4284898982 cites W3167544239 @default.
• W4284898982 cites W3172748993 @default.
• W4284898982 cites W3174694819 @default.
• W4284898982 cites W3182424782 @default.
• W4284898982 cites W3196415326 @default.
• W4284898982 cites W3202694701 @default.
• W4284898982 cites W3204770631 @default.
• W4284898982 cites W3206867763 @default.
• W4284898982 cites W3210328514 @default.
• W4284898982 cites W4211222514 @default.
• W4284898982 cites W4224145538 @default.
• W4284898982 cites W4245152641 @default.
• W4284898982 doi "https://doi.org/10.1155/2022/5075998" @default.
• W4284898982 hasPublicationYear "2022" @default.
• W4284898982 type Work @default.
• W4284898982 citedByCount "15" @default.
• W4284898982 countsByYear W42848989822022 @default.
• W4284898982 countsByYear W42848989822023 @default.
• W4284898982 crossrefType "journal-article" @default.
• W4284898982 hasAuthorship W4284898982A5001270995 @default.
• W4284898982 hasAuthorship W4284898982A5028422756 @default.
• W4284898982 hasAuthorship W4284898982A5035644463 @default.
• W4284898982 hasAuthorship W4284898982A5051779439 @default.
• W4284898982 hasBestOaLocation W42848989821 @default.
• W4284898982 hasConcept C11413529 @default.
• W4284898982 hasConcept C118615104 @default.
• W4284898982 hasConcept C118930307 @default.
• W4284898982 hasConcept C154945302 @default.
• W4284898982 hasConcept C177264268 @default.
• W4284898982 hasConcept C17744445 @default.
• W4284898982 hasConcept C178790620 @default.
• W4284898982 hasConcept C185592680 @default.
• W4284898982 hasConcept C199360897 @default.
• W4284898982 hasConcept C199539241 @default.
• W4284898982 hasConcept C20701700 @default.
• W4284898982 hasConcept C2780522230 @default.
• W4284898982 hasConcept C2781311116 @default.

• next