基于自适应蚁群算法的系统进化树构建

Ling Qin, Jianli Luo, Zhimin Chen, Jing Guo, Ling Chen, Yi Pan
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引用次数: 2

摘要

提出了一种基于给定对象(蛋白质、物种等)构建系统发育树的新方法。作为蚁群优化的扩展,该方法提出了一种基于有向图的自适应启发式系统发育聚类算法,以寻找在给定对象之间定义一定祖先关系的树状结构。在我们的方法中,给定的目标被蚁群聚类,这些聚类被用来逐步构建系统发育树。在算法的最后,由蚁群对这些系统进化树进行优化,以获得最适合给定对象的树。对我们的系统发育树构建方法进行了测试,并与遗传算法的结果进行了比较。实验结果表明,该算法实现简单,效率高。与遗传算法相比,该算法收敛速度更快,得到的结果质量更高
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Phelogenetic Tree Construction using Self adaptive Ant Colony Algorithm
A new phylogenetic tree construction method from a given set of objects (proteins, species, etc) is presented. As an extension of ant colony optimization, this method proposes an adaptive heuristic phylogenetic clustering algorithm based on a digraph to find a tree-like structure that defines certain ancestral relationships between the given objects. In our method, the given objects are clustered by the ant colony, and these clusters are used to construct phylogenetic trees progressively. In the end of the algorithm, these phylogenetic trees are optimized by the ant colony to get the fittest to the given objects. Our phylogenetic tree constructing method is tested to compare its results with that of the GA method. Experimental results show that our algorithm is easier to implement and more efficient. It can convergence faster and obtain higher quality results than GA
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