Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/6777
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dc.contributor.authorKumova, Bora İsmail-
dc.contributor.authorÇakır, Hüseyin-
dc.date.accessioned2018-02-13T07:33:36Z-
dc.date.available2018-02-13T07:33:36Z-
dc.date.issued2010-
dc.identifier.citationKumova, B. İ., and Çakır, H. (2010). The fuzzy syllogistic system. Lecture Notes in Computer Science, 6438 LNAI (PART 2), 418-427. doi:10.1007/978-3-642-16773-7_36en_US
dc.identifier.isbn9783642167720-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttp://doi.org/10.1007/978-3-642-16773-7_36-
dc.identifier.urihttp://hdl.handle.net/11147/6777-
dc.description9th Mexican International Conference on Artificial Intelligence, MICAI 2010; Pachuca; Mexico; 8 November 2010 through 13 November 2010en_US
dc.description.abstractA categorical syllogism is a rule of inference, consisting of two premisses and one conclusion. Every premiss and conclusion consists of dual relationships between the objects M, P, S. Logicians usually use only true syllogisms for deductive reasoning. After predicate logic had superseded syllogisms in the 19th century, interest on the syllogistic system vanished. We have analysed the syllogistic system, which consists of 256 syllogistic moods in total, algorithmically. We have discovered that the symmetric structure of syllogistic figure formation is inherited to the moods and their truth values, making the syllogistic system an inherently symmetric reasoning mechanism, consisting of 25 true, 100 unlikely, 6 uncertain, 100 likely and 25 false moods. In this contribution, we discuss the most significant statistical properties of the syllogistic system and define on top of that the fuzzy syllogistic system. The fuzzy syllogistic system allows for syllogistic approximate reasoning inductively learned M, P, S relationships.en_US
dc.description.sponsorship2009-İYTE-BAP-11en_US
dc.language.isoenen_US
dc.publisherSpringer Verlagen_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectApproximate reasoningen_US
dc.subjectAutomated reasoningen_US
dc.subjectSyllogistic reasoningen_US
dc.subjectFallaciesen_US
dc.titleThe fuzzy syllogistic systemen_US
dc.typeConference Objecten_US
dc.institutionauthorKumova, Bora İsmail-
dc.institutionauthorÇakır, Hüseyin-
dc.departmentİzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.volume6438 LNAIen_US
dc.identifier.issuePART 2en_US
dc.identifier.startpage418en_US
dc.identifier.endpage427en_US
dc.identifier.wosWOS:000320533000036en_US
dc.identifier.scopus2-s2.0-78649997932en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1007/978-3-642-16773-7_36-
dc.relation.doi10.1007/978-3-642-16773-7_36en_US
dc.coverage.doi10.1007/978-3-642-16773-7_36en_US
local.message.claim2022-06-03T09:59:53.878+0300|||rp02905|||submit_approve|||dc_contributor_author|||None*
dc.identifier.scopusqualityQ2-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairetypeConference Object-
crisitem.author.dept03.04. Department of Computer Engineering-
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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