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Please use this identifier to cite or link to this item: http://hdl.handle.net/UCSP/15789
Title: FP-AK-QIEAR-R in protein folding application
Authors: Chire Saire, Josimar Edinson
Túpac Valdivia, Yván Jesús
Keywords: Artificial intelligence;Iterative methods;Probability density function;Protein folding;Proteins;Benchmark functions;Evolutionary operations;Initial population;Particle filter;PDF estimation;Quantum inspired evolutionary algorithm;Real applications;Evolutionary algorithms
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
metadata.dc.relation.uri: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018172603&doi=10.1109%2fLA-CCI.2016.7885726&partnerID=40&md5=72c5c4a4284e6c8b7941f6fbcaf02bfb
Abstract: There are many Evolutionary Algorithms which main features are: population, evolutionary operations (crossover, mate, mutation and others). Most of them are based on randomness and follow a criteria using fitness like selector. The proposal uses probability density function according to best of initial population to sample new population and save better individuals iteratively. Then using centroid criteria sample for every dimension and get better individuals. It had good results with benchmark functions. A real application was performed with experiments in protein folding and it showed good results. © 2016 IEEE.
URI: http://repositorio.ucsp.edu.pe/handle/UCSP/15789
ISBN: 9781509051052
Appears in Collections:Artículos de investigación

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