Mi DSpace
Please use this identifier to cite or link to this item: http://hdl.handle.net/UCSP/15834
Title: An approach to real-coded quantum inspired evolutionary algorithm using particles filter
Authors: Chire Saire, Josimar Edinson
Túpac Valdivia, Yván Jesús
Keywords: Algorithms;Artificial intelligence;Bandpass filters;Distributed computer systems;Function evaluation;Monte Carlo methods;Optimization;Probability density function;Quantum theory;Signal filtering and prediction;Target tracking;Benchmark functions;Combined mechanisms;Multi-linear regression;Particle filter;PDF estimation;Quantum inspired evolutionary algorithm;Quantum superpositions;Relative frequencies;Evolutionary algorithms
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
metadata.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
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.
URI: http://repositorio.ucsp.edu.pe/handle/UCSP/15834
ISBN: urn:isbn:9781467384186
Appears in Collections:Artículos - Ciencia de la computación

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.