Fuzzy cognitive maps learning through swarm intelligence

dc.contributor.authorPapageorgiou, E. I.en
dc.contributor.authorParsopoulos, K. E.en
dc.contributor.authorGroumpos, P. P.en
dc.contributor.authorVrahatis, M. N.en
dc.date.accessioned2015-11-24T17:00:49Z
dc.date.available2015-11-24T17:00:49Z
dc.identifier.issn0302-9743-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/10821
dc.rightsDefault Licence-
dc.titleFuzzy cognitive maps learning through swarm intelligenceen
heal.abstractA technique for Fuzzy Cognitive Maps learning, which is based on the minimization of a properly defined objective function using the Particle Swarm Optimization algorithm, is presented. The workings of the technique are illustrated on an industrial process control problem. The obtained results support the claim that swarm intelligence algorithms can be a valuable tool for Fuzzy Cognitive Maps learning, alleviating deficiencies of Fuzzy Cognitive Maps, and controlling the system's convergence.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.journalNameArtificial Intelligence and Soft Computing - Icaisc 2004en
heal.journalTypepeer reviewed-
heal.languageen-
heal.publicationDate2004-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικήςel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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