A hybrid of bacterial foraging and differential evolution -based distance of sequences

被引:3
|
作者
Fuad, Muhammad Marwan Muhammad [1 ]
机构
[1] Univ Tromso, NO-9037 Tromso, Norway
来源
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS 18TH ANNUAL CONFERENCE, KES-2014 | 2014年 / 35卷
关键词
Bacterial Foraging; Differential Evolution; Sigma Gram Distance; OPTIMIZATION; SYNERGY;
D O I
10.1016/j.procs.2014.08.089
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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. (C) 2014 The Authors. Published by Elsevier B.V.
引用
收藏
页码:101 / 110
页数:10
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