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dc.contributor.authorLiang, Haiming
dc.contributor.authorDong, Yucheng
dc.contributor.authorUreña, Raquel
dc.contributor.authorChiclana, Francisco
dc.contributor.authorHerrera-Viedma, Enrique
dc.contributor.authorDing, Zhaogang
dc.date.accessioned2019-09-10T08:58:36Z
dc.date.available2019-09-10T08:58:36Z
dc.date.issued2019-09-06
dc.identifier.citationLiang, H., Dong, Y., Ding, Z., Ureña, R., Chiclana, F., Herrera-Viedma, E. (2019) Consensus Reaching with Time Constraints and Minimum Adjustments in Group with Bounded Confidence Effects. IEEE Transactions on Fuzzy Systems,en
dc.identifier.issn1063-6706
dc.identifier.urihttps://www.dora.dmu.ac.uk/handle/2086/18423
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.en
dc.description.abstractIn the bounded confidence model it is widely known that individuals rely on the opinions of their close friends or people with similar interests. Meanwhile, the decision maker always hopes that the opinions of individuals can reach a consensus in a required time. Therefore, with this idea in mind, this paper develops a consensus reaching model with time constraints and minimum adjustments in a group with bounded confidence effects. In the proposed consensus approach, the minimum adjustments rule is used to modify the initial opinions of individuals with bounded confidence, which can further influence the opinion evolutions of individuals to reach a consensus in a required time. The properties of the model are studied, and detailed numerical examples and comparative simulation analysis are provided to justify its feasibility.en
dc.language.isoenen
dc.publisherIEEEXploreen
dc.subjectConsensusen
dc.subjecttime constraintsen
dc.subjectbounded confidenceen
dc.subjectminimum adjustmentsen
dc.subjectopinion dynamicsen
dc.subjectgroup decision makingen
dc.titleConsensus Reaching with Time Constraints and Minimum Adjustments in Group with Bounded Confidence Effectsen
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1109/tfuzz.2019.2939970
dc.peerreviewedYesen
dc.funderEuropean Union (EU) Horizon 2020en
dc.projectidH2020-MSCA-IF-2016- DeciTrustNET-746398en
dc.projectid71871149, 71571124, 71971149 and 71601133en
dc.projectidsksyl201705, 2018hhs-58 and YJ201906en
dc.projectidTIN2016-75850-Ren
dc.cclicenceCC-BY-NC-NDen
dc.date.acceptance2019-08-13
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.funder.otherNSF of Chinaen
dc.funder.otherSichuan Universityen
dc.funder.otherFEDER funds provided in the National Spanish projecten


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