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dc.contributor.authorGuo, Sandang
dc.contributor.authorLi, Ye
dc.contributor.authorDong, Fenyi
dc.contributor.authorLi, Bingjun
dc.contributor.authorYang, Yingjie
dc.date.accessioned2019-07-18T13:13:09Z
dc.date.available2019-07-18T13:13:09Z
dc.date.issued2019
dc.identifier.citationGuo, S., Li, Y., Dong, F., Li, B. and Yang, Y. (2019) Multi-attribute Grey Target Decision-making Based on "Kernel" and Double Degree of Greyness. Journal of Grey System, 31(2), pp.27-36.en
dc.identifier.issn2396-9040
dc.identifier.urihttps://www.dora.dmu.ac.uk/handle/2086/18245
dc.descriptionThe file attached to this record is the Publisher's final version.en
dc.description.abstractAccording to the characteristics of three-parameter interval grey number and the advantages of grey target, a multi-attribute grey target decision-making method is built. First, the "kernel" of the three-parameter interval grey number based on the most probability' is defined, and the upper bound degree of greyness and the lower bound degree of greyness are separately defined for the asymmetry on the two sides, then the distance measure formula affected by the risk attitude of the decision maker is given. Considering the proximity of schemes to the optimal vector and the worst vector, the comprehensive off-target distances and their space projection on the line connecting the point of the positive bull's eye and the negative bull's eye are obtained, and the ranking of the schemes is ultimately determined. Finally, an example validates the rationality and effectiveness of the method, which may provide a new way of thinking in terms of research on grey decision-making theory and application.en
dc.language.isoenen
dc.publisherResearch Information Ltden
dc.subject"Kernel"en
dc.subjectDouble Degree of Greynessen
dc.subjectMulti-attribute Grey Target Decision-makingen
dc.subjectThree-parameter Interval Grey Numberen
dc.titleMulti-attribute Grey Target Decision-making Based on" Kernel" and Double Degree of Greynessen
dc.typeArticleen
dc.peerreviewedYesen
dc.funderNo external funderen
dc.projectidRoyal Society: IEC\NSFC\170391en
dc.cclicenceCC-BY-NCen
dc.date.acceptance2018-11-22
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.funder.otherRoyal Societyen


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