| 基于SWGPSO算法的多序列比对 |
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| 引用本文： | 徐小俊,雷秀娟,郭玲. 基于SWGPSO算法的多序列比对[J]. 计算机工程, 2011, 37(6): 184-186. DOI: 10.3969/j.issn.1000-3428.2011.06.063 |
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| 作者姓名： | 徐小俊 雷秀娟 郭玲 |
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| 作者单位： | 1. 陕西师范大学计算机科学学院,西安,710062
2. 陕西师范大学生命科学学院,西安,710062 |
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| 基金项目： | 中央高校基本科研业务专项基金资助项目，2010年度陕西省科技计划基金资助项目 |
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| 摘 要： | 针对粒子群优化(PSO)易陷入局部最优、收敛速度慢的现象，提出一种新的惯性权重取值方法——分段取值惯性权重(SW)方法。该方法在算法前期增加粒子多样性，后期加速算法收敛。针对PSO仅使用2个最优值寻优的问题，引入第3个最优值GB，将SW与GB结合，改进PSO的进化方程。实验结果表明，该算法解决多序列比对问题时，可以有效地避免算法早熟，并提高解的精度。
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| 关 键 词： | 粒子群优化算法 分段取值惯性权重 SW与GB的结合 |
Multiple Sequence Alignment Based on SWGPSO Algorithm |
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| XU Xiao-jun,LEI Xiu-juan,GUO Ling. Multiple Sequence Alignment Based on SWGPSO Algorithm[J]. Computer Engineering, 2011, 37(6): 184-186. DOI: 10.3969/j.issn.1000-3428.2011.06.063 |
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| Authors: | XU Xiao-jun LEI Xiu-juan GUO Ling |
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| Affiliation: | b(a.School of Computer Science;b.College of Life Sciences,Shaanxi Normal University,Xi’an 710062,China) |
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| Abstract: | In this paper,a new method of getting inertia weight,Subsection Weight（SW） is proposed in order to solve the Particle Swarm Optimization（PSO） disadvantages which are likely to fall into local optimum and slow converge.The diversity of swarm increases at the prophase and the convergence is accelerated in the later period.Meanwhile,the combination of SW and GB can improve the evolutionary equation of PSO and makes it perform better.Experimental result shows that the algorithm can effectively avoid converging too early and increase the precision in solving multiple sequence alignment. |
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| Keywords: | Particle Swarm Optimization（PSO） algorithm Subsection Weight（SW） combination of SW and GB |
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