Publication
Fuzzy rule extraction by bacterial memetic algorithms
dc.contributor.author | Botzheim, J. | |
dc.contributor.author | Cabrita, Cristiano Lourenço | |
dc.contributor.author | Kóczy, László T. | |
dc.contributor.author | Ruano, Antonio | |
dc.date.accessioned | 2013-02-06T14:42:46Z | |
dc.date.available | 2013-02-06T14:42:46Z | |
dc.date.issued | 2009 | |
dc.date.updated | 2013-01-26T17:29:24Z | |
dc.description.abstract | In our previous papers, fuzzy model identification methods were discussed. The bacterial evolutionary algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg–Marquardt method was also proposed for determining membership functions in fuzzy systems. The combination of the evolutionary and the gradient-based learning techniques is usually called memetic algorithm. In this paper, a new kind of memetic algorithm, the bacterial memetic algorithm, is introduced for fuzzy rule extraction. The paper presents how the bacterial evolutionary algorithm can be improved with the Levenberg–Marquardt technique. | por |
dc.identifier.citation | Botzheim, J.; Cabrita, C.; Kóczy, L. T.; Ruano, A. E. Fuzzy rule extraction by bacterial memetic algorithms, International Journal of Intelligent Systems, 24, 3, 312-339, 2009. | por |
dc.identifier.doi | http://dx.doi.org710.1002/int.20338 | |
dc.identifier.issn | 08848173 | |
dc.identifier.other | AUT: ARU00698; CCA01443; | |
dc.identifier.uri | http://hdl.handle.net/10400.1/2237 | |
dc.language.iso | eng | por |
dc.peerreviewed | yes | por |
dc.title | Fuzzy rule extraction by bacterial memetic algorithms | por |
dc.type | journal article | |
dspace.entity.type | Publication | |
oaire.citation.endPage | 339 | por |
oaire.citation.issue | 2 | por |
oaire.citation.startPage | 312 | por |
oaire.citation.title | International Journal of Intelligent Systems | por |
oaire.citation.volume | 24 | por |
person.familyName | Cabrita | |
person.familyName | Ruano | |
person.givenName | Cristiano Lourenço | |
person.givenName | Antonio | |
person.identifier.ciencia-id | FF1E-13A0-A269 | |
person.identifier.orcid | 0000-0003-4946-0465 | |
person.identifier.orcid | 0000-0002-6308-8666 | |
person.identifier.rid | B-4135-2008 | |
person.identifier.scopus-author-id | 55958626100 | |
person.identifier.scopus-author-id | 7004284159 | |
rcaap.rights | restrictedAccess | por |
rcaap.type | article | por |
relation.isAuthorOfPublication | 081b091f-c9fa-470a-9a28-51fe4c85864a | |
relation.isAuthorOfPublication | 13813664-b68b-40aa-97a9-91481a31ebf2 | |
relation.isAuthorOfPublication.latestForDiscovery | 081b091f-c9fa-470a-9a28-51fe4c85864a |