Sparse fuzzy systems generation and fuzzy rule interpolation: A practical approach

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dc.contributor.authorChongen
dc.contributor.authorGedeon, T. D.en
dc.contributor.authorKovacs, Szen
dc.contributor.authorKoczy, L. T.en
dc.date.accessioned2025-12-31T21:41:46Z
dc.date.available2025-12-31T21:41:46Z
dc.date.issued2003en
dc.description.abstractIn this paper, we explore the use of a sparse fuzzy system generation technique in conjunction with simple projection-based fuzzy rule interpolation, to generate sparse fuzzy systems with relatively few rules whilst still achieving reasonable system accuracy. Through setting a parameter value, the user is able to control, to some extent, the number of rules generated by the rule extraction technique. The rule interpolation approach enables the sparse fuzzy system to maintain a reasonable accuracy. The effectiveness of this approach is validated experimentally.en
dc.description.statusPeer-revieweden
dc.format.extent6en
dc.identifier.scopus0038537483en
dc.identifier.urihttps://hdl.handle.net/1885/733798223
dc.language.isoenen
dc.relation.ispartofseriesThe IEEE International conference on Fuzzy Systemsen
dc.titleSparse fuzzy systems generation and fuzzy rule interpolation: A practical approachen
dc.typeConference paperen
dspace.entity.typePublicationen
local.bibliographicCitation.lastpage499en
local.bibliographicCitation.startpage494en
local.contributor.affiliationGedeon, T. D.; School of Computing, ANU College of Systems and Society, The Australian National Universityen
local.contributor.affiliationKovacs, Sz; Budapest University of Technology and Economicsen
local.contributor.affiliationKoczy, L. T.; University of Miskolcen
local.identifier.ariespublicationU3594520xPUB103en
local.identifier.purec80d6899-26e7-4bdd-abd8-ff806febbef1en
local.identifier.urlhttps://www.scopus.com/pages/publications/0038537483en
local.type.statusPublisheden

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