Type-1 OWA Operators in Aggregating Multiple Sources of Uncertain Information: Properties and Real-World Applications in Integrated Diagnosis.

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dc.cclicenceCC-BY-NCen
dc.contributor.authorZhou, Shangming
dc.contributor.authorChiclana, Francisco
dc.contributor.authorJohn, Robert
dc.contributor.authorGaribaldi, Jonathan
dc.contributor.authorHuo, Lin
dc.date.acceptance2020-04-27
dc.date.accessioned2021-09-01T13:55:55Z
dc.date.available2021-09-01T13:55:55Z
dc.date.issued2021-05-06
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.abstractThe type-1 ordered weighted averaging (T1OWA) operator has demonstrated the capacity for directly aggregating multiple sources of linguistic information modeled by fuzzy sets rather than crisp values. Yager's ordered weighted averaging (OWA) operators possess the properties of idempotence, monotonicity, compensativeness, and commutativity . This article aims to address whether or not T1OWA operators possess these properties when the inputs and associated weights are fuzzy sets instead of crisp numbers. To this end, a partially ordered relation of fuzzy sets is defined based on the fuzzy maximum ( join ) and fuzzy minimum ( meet ) operators of fuzzy sets, and an alpha-equivalently-ordered relation of groups of fuzzy sets is proposed. Moreover, as the extension of orness and andness of an Yager's OWA operator, joinness and meetness of a T1OWA operator are formalized, respectively. Then, based on these concepts and the representation theorem of T1OWA operators , we prove that T1OWA operators hold the same properties as Yager's OWA operators possess, i.e., idempotence, monotonicity, compensativeness, and commutativity . Various numerical examples and a case study of diabetes diagnosis are provided to validate the theoretical analyses of these properties in aggregating multiple sources of uncertain information and improving integrated diagnosis, respectively.en
dc.exception.reasonnot deposited within 3 months of publicationen
dc.funderNo external funderen
dc.identifier.citationZhou, S., Chiclana, F., John, R., Garibaldi, J. and Huo, L. (2021) Type-1 OWA Operators in Aggregating Multiple Sources of Uncertain Information: Properties and Real-World Applications in Integrated Diagnosis. IEEE Transactions on Fuzzy Systems, 29, (8), pp. 2112-2121en
dc.identifier.doihttps://doi.org/10.1109/TFUZZ.2020.2992909
dc.identifier.urihttps://dora.dmu.ac.uk/handle/2086/21226
dc.language.isoenen
dc.peerreviewedYesen
dc.publisherIEEEen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en
dc.titleType-1 OWA Operators in Aggregating Multiple Sources of Uncertain Information: Properties and Real-World Applications in Integrated Diagnosis.en
dc.typeArticleen

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