Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/9266
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dc.contributor.authorRudas I.en
dc.contributor.authorPap E.en
dc.contributor.authorFodor J.en
dc.date.accessioned2019-09-30T09:14:41Z-
dc.date.available2019-09-30T09:14:41Z-
dc.date.issued2013-01-01en
dc.identifier.issn09507051en
dc.identifier.urihttps://open.uns.ac.rs/handle/123456789/9266-
dc.description.abstractThis paper offers a comprehensive study of information aggregation in intelligent systems prompted by common engineering interest. After a motivating introduction we consider aggregation functions and their fundamental properties as a basis for further development. Four main classes of aggregation functions are identified, and important subclasses are described and characterized as prototypes. For practical purposes, we outline two procedures to identify aggregation function that fits best to empirical data. Finally, we briefly recall some applications of aggregation functions in decision making, utility theory, fuzzy inference systems, multisensor data fusion, image processing, and their hardware implementation. © 2012 Elsevier B.V. All rights reserved.en
dc.relation.ispartofKnowledge-Based Systemsen
dc.titleInformation aggregation in intelligent systems: An application oriented approachen
dc.typeJournal/Magazine Articleen
dc.identifier.doi10.1016/j.knosys.2012.07.025en
dc.identifier.scopus2-s2.0-84871589854en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84871589854en
dc.relation.lastpage13en
dc.relation.firstpage3en
dc.relation.volume38en
item.grantfulltextnone-
item.fulltextNo Fulltext-
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