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Bacterial memetic algorithm for fuzzy rule base optimization

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dc.contributor.authorCabrita, Cristiano
dc.contributor.authorBotzheim, Janos
dc.contributor.authorGedeon, Tamas (Tom)
dc.contributor.authorRuano, Antonio E
dc.contributor.authorFonseca, Carlos
dc.contributor.authorKoczy, Lazlo
dc.coverage.spatialBudapest Hungary
dc.date.accessioned2015-12-08T22:40:38Z
dc.date.createdJuly 24-26 2006
dc.date.issued2006
dc.date.updated2015-12-08T10:25:12Z
dc.description.abstractIn our previous works model identification methods were discussed. The bacterial evolutionary algorithm for extracting a fuzzy rule base from a training set was presented. The LevenbergMarquardt method was also proposed for determining membership functions in fuzzy systems. The combination of evolutionary and gradient-based learning techniques - the bacterial memetic algorithm - was also introduced. In this paper an improvement of the bacterial memetic algorithm is shown for fuzzy rule extraction. The new method can optimize not only the rules, but can also find the optimal size of the rule base.
dc.identifier.urihttp://hdl.handle.net/1885/36583
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.relation.ispartofseriesWorld Automation Conference (WAC 2006)
dc.sourceProceedings of World Automation Conference 2006
dc.subjectKeywords: Bacteria; Functions; Fuzzy rules; Learning algorithms; Logic programming; Optimization; Bacterial algorithms; Fuzzy rule base; Levenberg-marquardt methods; Memetic algorithms; Evolutionary algorithms Bacterial algorithm; Fuzzy rule base; Levenberg-marquardt method; Memetic algorithm
dc.titleBacterial memetic algorithm for fuzzy rule base optimization
dc.typeConference paper
local.bibliographicCitation.startpage6
local.contributor.affiliationCabrita, Cristiano, University of Algarve
local.contributor.affiliationBotzheim, Janos, Budapest University of Technology and Economics
local.contributor.affiliationGedeon, Tamas (Tom), College of Engineering and Computer Science, ANU
local.contributor.affiliationRuano, Antonio E, University of Algarve
local.contributor.affiliationFonseca, Carlos, University of Algarve
local.contributor.affiliationKoczy, Lazlo, Budapest University of Technology and Economics
local.contributor.authoruidGedeon, Tamas (Tom), u4088783
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080108 - Neural, Evolutionary and Fuzzy Computation
local.identifier.absseo890299 - Computer Software and Services not elsewhere classified
local.identifier.ariespublicationu4251866xPUB138
local.identifier.doi10.1109/WAC.2006.376057
local.identifier.scopusID2-s2.0-36849000701
local.type.statusPublished Version

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