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Please use this identifier to cite or link to this item: http://hdl.handle.net/UCSP/15834
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dc.contributor.authorChire Saire, Josimar Edinson-
dc.contributor.authorTúpac Valdivia, Yván Jesús-
dc.date.accessioned2019-01-29T22:19:53Z-
dc.date.available2019-01-29T22:19:53Z-
dc.date.issued2016-
dc.identifier.isbn9781467384186es_PE
dc.identifier.urihttp://repositorio.ucsp.edu.pe/handle/UCSP/15834-
dc.description.abstractThis work proposes, implements and evaluates the FP-QIEA-R model as a new quantum inspired evolutionary algorithm based on the concept of quantum superposition that allows the optimization process to be carried on with a smaller number of evaluations. This model is based on a QIEA-R, but instead of just using quantum individuals based on uniform probability density functions, where the update consists on change the width and mean of each pdf; this proposal uses a combined mechanism inspired in particle filter and multilinear regression, re-sampling and relative frequency with the QIEA-R to estimate the probability density functions in a better way. To evaluate this proposal, some experiments under benchmark functions are presented. The obtained statistics from the outcomes show the improved performance of this proposal optimizing numerical problems. © 2015 IEEE.es_PE
dc.description.uriTrabajo de investigaciónes_PE
dc.language.isoenges_PE
dc.publisherInstitute of Electrical and Electronics Engineers Inc.es_PE
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84969626836&doi=10.1109%2fLA-CCI.2015.7435984&partnerID=40&md5=c55427a8b3c28835d0b3cb44373f5a54es_PE
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_PE
dc.sourceRepositorio Institucional - UCSPes_PE
dc.sourceUniversidad Católica San Pabloes_PE
dc.sourceScopuses_PE
dc.subjectAlgorithmses_PE
dc.subjectArtificial intelligencees_PE
dc.subjectBandpass filterses_PE
dc.subjectDistributed computer systemses_PE
dc.subjectFunction evaluationes_PE
dc.subjectMonte Carlo methodses_PE
dc.subjectOptimizationes_PE
dc.subjectProbability density functiones_PE
dc.subjectQuantum theoryes_PE
dc.subjectSignal filtering and predictiones_PE
dc.subjectTarget trackinges_PE
dc.subjectBenchmark functionses_PE
dc.subjectCombined mechanismses_PE
dc.subjectMulti-linear regressiones_PE
dc.subjectParticle filteres_PE
dc.subjectPDF estimationes_PE
dc.subjectQuantum inspired evolutionary algorithmes_PE
dc.subjectQuantum superpositionses_PE
dc.subjectRelative frequencieses_PE
dc.subjectEvolutionary algorithmses_PE
dc.titleAn approach to real-coded quantum inspired evolutionary algorithm using particles filteres_PE
dc.typeinfo:eu-repo/semantics/conferenceObjectes_PE
dc.identifier.doi10.1109/LA-CCI.2015.7435984es_PE
Appears in Collections:Artículos de investigación

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