Matches in SemOpenAlex for { <https://semopenalex.org/work/W2610830042> ?p ?o ?g. }
- W2610830042 endingPage "468" @default.
- W2610830042 startingPage "459" @default.
- W2610830042 abstract "This article proposes an algorithmic approach for group decision making (GDM) problems using neutrosophic soft matrix (NSM) and relative weights of experts. NSM is the matrix representation of neutrosophic soft sets (NSSs), where NSS is the combination of neutrosophic set and soft set. We propose a new idea for assigning relative weights to the experts based on cardinalities of NSSs. The relative weight is assigned to each of the experts based on their preferred attributes and opinions, which reduces the chance of unfairness in the decision making process. Firstly we introduce choice matrix and combined choice matrix using neutrosophic sets. Multiplying combined choice matrices with the individual NSMs, this study develops product NSMs, which are aggregated to find out the collective NSM. Then neutrosophic cross-entropy measure is used to rank the alternatives and for selecting the most desirable one(s). This study also provides a comparative analysis of the proposed weight based approach with the normal procedure, where weight is not considered. Finally, a case study illustrates the applicability of the proposed approach." @default.
- W2610830042 created "2017-05-12" @default.
- W2610830042 creator A5009018152 @default.
- W2610830042 creator A5039040767 @default.
- W2610830042 creator A5050650296 @default.
- W2610830042 creator A5081476268 @default.
- W2610830042 date "2019-10-01" @default.
- W2610830042 modified "2023-10-16" @default.
- W2610830042 title "Group decision making using neutrosophic soft matrix: An algorithmic approach" @default.
- W2610830042 cites W1578428442 @default.
- W2610830042 cites W1595461165 @default.
- W2610830042 cites W1900036544 @default.
- W2610830042 cites W1978352585 @default.
- W2610830042 cites W1979697961 @default.
- W2610830042 cites W1980564456 @default.
- W2610830042 cites W2000763566 @default.
- W2610830042 cites W2019271682 @default.
- W2610830042 cites W2031241748 @default.
- W2610830042 cites W2038190934 @default.
- W2610830042 cites W2040121225 @default.
- W2610830042 cites W2056788985 @default.
- W2610830042 cites W2057222675 @default.
- W2610830042 cites W2062612670 @default.
- W2610830042 cites W2063170755 @default.
- W2610830042 cites W2068402605 @default.
- W2610830042 cites W2113668671 @default.
- W2610830042 cites W2136692556 @default.
- W2610830042 cites W2138967295 @default.
- W2610830042 cites W2153696615 @default.
- W2610830042 cites W2285988136 @default.
- W2610830042 cites W2339111061 @default.
- W2610830042 cites W2464540213 @default.
- W2610830042 cites W2474649570 @default.
- W2610830042 cites W2517165124 @default.
- W2610830042 cites W2544090818 @default.
- W2610830042 cites W2574155231 @default.
- W2610830042 cites W2582730511 @default.
- W2610830042 cites W2964177077 @default.
- W2610830042 cites W3150277910 @default.
- W2610830042 cites W4211007335 @default.
- W2610830042 cites W4361868917 @default.
- W2610830042 doi "https://doi.org/10.1016/j.jksuci.2017.05.001" @default.
- W2610830042 hasPublicationYear "2019" @default.
- W2610830042 type Work @default.
- W2610830042 sameAs 2610830042 @default.
- W2610830042 citedByCount "17" @default.
- W2610830042 countsByYear W26108300422018 @default.
- W2610830042 countsByYear W26108300422019 @default.
- W2610830042 countsByYear W26108300422020 @default.
- W2610830042 countsByYear W26108300422021 @default.
- W2610830042 countsByYear W26108300422022 @default.
- W2610830042 countsByYear W26108300422023 @default.
- W2610830042 crossrefType "journal-article" @default.
- W2610830042 hasAuthorship W2610830042A5009018152 @default.
- W2610830042 hasAuthorship W2610830042A5039040767 @default.
- W2610830042 hasAuthorship W2610830042A5050650296 @default.
- W2610830042 hasAuthorship W2610830042A5081476268 @default.
- W2610830042 hasBestOaLocation W26108300421 @default.
- W2610830042 hasConcept C103275481 @default.
- W2610830042 hasConcept C106301342 @default.
- W2610830042 hasConcept C106487976 @default.
- W2610830042 hasConcept C114614502 @default.
- W2610830042 hasConcept C121332964 @default.
- W2610830042 hasConcept C124101348 @default.
- W2610830042 hasConcept C154945302 @default.
- W2610830042 hasConcept C159985019 @default.
- W2610830042 hasConcept C164226766 @default.
- W2610830042 hasConcept C177264268 @default.
- W2610830042 hasConcept C17744445 @default.
- W2610830042 hasConcept C178790620 @default.
- W2610830042 hasConcept C185592680 @default.
- W2610830042 hasConcept C192562407 @default.
- W2610830042 hasConcept C199360897 @default.
- W2610830042 hasConcept C199539241 @default.
- W2610830042 hasConcept C20701700 @default.
- W2610830042 hasConcept C2776359362 @default.
- W2610830042 hasConcept C2777037408 @default.
- W2610830042 hasConcept C2780009758 @default.
- W2610830042 hasConcept C2781311116 @default.
- W2610830042 hasConcept C33923547 @default.
- W2610830042 hasConcept C41008148 @default.
- W2610830042 hasConcept C58166 @default.
- W2610830042 hasConcept C62520636 @default.
- W2610830042 hasConcept C94625758 @default.
- W2610830042 hasConceptScore W2610830042C103275481 @default.
- W2610830042 hasConceptScore W2610830042C106301342 @default.
- W2610830042 hasConceptScore W2610830042C106487976 @default.
- W2610830042 hasConceptScore W2610830042C114614502 @default.
- W2610830042 hasConceptScore W2610830042C121332964 @default.
- W2610830042 hasConceptScore W2610830042C124101348 @default.
- W2610830042 hasConceptScore W2610830042C154945302 @default.
- W2610830042 hasConceptScore W2610830042C159985019 @default.
- W2610830042 hasConceptScore W2610830042C164226766 @default.
- W2610830042 hasConceptScore W2610830042C177264268 @default.
- W2610830042 hasConceptScore W2610830042C17744445 @default.
- W2610830042 hasConceptScore W2610830042C178790620 @default.
- W2610830042 hasConceptScore W2610830042C185592680 @default.
- W2610830042 hasConceptScore W2610830042C192562407 @default.