| 新型粒子群优化算法在多序列联配中的应用 |
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| 引用本文： | 胡桂武. 新型粒子群优化算法在多序列联配中的应用[J]. 生物信息学, 2008, 6(1): 22-24 |
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| 作者姓名： | 胡桂武 |
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| 作者单位： | 广东商学院数学与计算科学系,广东,广州,510320 |
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| 摘 要： | 将粒子群优化算法应用于序列联配，提出了一种改进的粒子群优化算法，该算法在粒子群的进化过程中根据粒子的适应值动态地调整粒子群的惯性权重与粒子群飞行速度范围，提高了算法的收敛速度和收敛精度；针对PSO算法可能出现的早熟现象，引入重新初始化机制，增强了算法的搜索能力，实验表明该算法是有效的。
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| 关 键 词： | 多序列联配 粒子群优化 生物信息学 群智能 进化计算 |
| 文章编号： | 1672-5565（2008）-01-22-03 |
| 收稿时间： | 2006-10-25 |
| 修稿时间： | 2006-11-29 |
A novel partical swarm optimization and its application to multiple Sequence alignment |
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| HU Gui-wu. A novel partical swarm optimization and its application to multiple Sequence alignment[J]. Chinese Journal of Bioinformatics, 2008, 6(1): 22-24 |
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| Authors: | HU Gui-wu |
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| Affiliation: | HU Gui - wu ( Department of Mathematics Computational Scienve , Guangdong Business College, Guangzhou 510320, China ) |
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| Abstract: | In this paper, an improved PSO is applied for sequence alignment. Based on the best fitness of the particles, the ranges of both inertia weights and velocity of the particles are adjusted dynamically with the evolution of particle swarm in the algorithm, which will improve the convergence speed and precision. To avoid the possible prematurity of PSO, the reinitialization mechanism is introduced in algorithm which increases the search power of PSO. Experiment shows the algorithm is effective. |
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| Keywords: | Multiple sequence alignment Particle swarm optimization Bioinformatics Swarm intelligence Evolutionary computation |
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