A Hybrid of Bacterial Foraging and Differential Evolution -based Distance of Sequences

In a previous work we presented a new distance that we called the sigma gram distance, which is used to compute the similarity between two sequences. This distance is based on parameters which we computed through an optimization process that used the artificial bee colony; a bio-inspired optimizatio...

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Bibliographic Details
Published in:Procedia computer science 2014, Vol.35, p.101-110
Main Author: Fuad, Muhammad Marwan Muhammad
Format: Article
Language:English
Subjects:
422:Algorithms and computability theory
422:Algoritmer og beregnbarhetsteori
Bacterial Foraging
Differential Evolution
Sigma Gram Distance
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Summary:In a previous work we presented a new distance that we called the sigma gram distance, which is used to compute the similarity between two sequences. This distance is based on parameters which we computed through an optimization process that used the artificial bee colony; a bio-inspired optimization algorithm. In this paper we show how a hybrid of two optimization algorithms; bacterial foraging and differential evolution, when used to compute the parameters of the sigma gram distance, can yield better results than those obtained by applying artificial bee colony. This superiority in performance is validated through experiments on the same data sets to which artificial bee colony, on the same optimization problem, was tested.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2014.08.089