An approach to real-coded quantum inspired evolutionary algorithm using particles filter
dc.contributor.author | Chire Saire, Josimar Edinson | |
dc.contributor.author | Túpac Valdivia, Yván Jesús | |
dc.date.accessioned | 2019-01-29T22:19:53Z | |
dc.date.available | 2019-01-29T22:19:53Z | |
dc.date.issued | 2016 | |
dc.description.abstract | This 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.uri | Trabajo de investigación | es_PE |
dc.identifier.doi | https://doi.org/10.1109/LA-CCI.2015.7435984 | es_PE |
dc.identifier.isbn | urn:isbn:9781467384186 | es_PE |
dc.identifier.uri | https://hdl.handle.net/20.500.12590/15834 | |
dc.language.iso | eng | es_PE |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | es_PE |
dc.relation.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969626836&doi=10.1109%2fLA-CCI.2015.7435984&partnerID=40&md5=c55427a8b3c28835d0b3cb44373f5a54 | es_PE |
dc.rights | info:eu-repo/semantics/restrictedAccess | es_PE |
dc.source | Repositorio Institucional - UCSP | es_PE |
dc.source | Universidad Católica San Pablo | es_PE |
dc.source | Scopus | es_PE |
dc.subject | Algorithms | es_PE |
dc.subject | Artificial intelligence | es_PE |
dc.subject | Bandpass filters | es_PE |
dc.subject | Distributed computer systems | es_PE |
dc.subject | Function evaluation | es_PE |
dc.subject | Monte Carlo methods | es_PE |
dc.subject | Optimization | es_PE |
dc.subject | Probability density function | es_PE |
dc.subject | Quantum theory | es_PE |
dc.subject | Signal filtering and prediction | es_PE |
dc.subject | Target tracking | es_PE |
dc.subject | Benchmark functions | es_PE |
dc.subject | Combined mechanisms | es_PE |
dc.subject | Multi-linear regression | es_PE |
dc.subject | Particle filter | es_PE |
dc.subject | PDF estimation | es_PE |
dc.subject | Quantum inspired evolutionary algorithm | es_PE |
dc.subject | Quantum superpositions | es_PE |
dc.subject | Relative frequencies | es_PE |
dc.subject | Evolutionary algorithms | es_PE |
dc.subject.ocde | https://purl.org/pe-repo/ocde/ford#1.02.00 | es_PE |
dc.title | An approach to real-coded quantum inspired evolutionary algorithm using particles filter | es_PE |
dc.type | info:eu-repo/semantics/conferenceObject |