作者投稿和查稿 主编审稿 专家审稿 编委审稿 远程编辑

计算机工程 ›› 2008, Vol. 34 ›› Issue (11): 12-14. doi: 10.3969/j.issn.1000-3428.2008.11.005

• 博士论文 • 上一篇    下一篇

基于迁徙差分进化算法集成的模体识别

胡桂武   

  1. (广东商学院数学与计算科学系,广州 510320)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-06-05 发布日期:2008-06-05

Motif Detection Based on Migration Differential Evolution Ensemble

HU Gui-wu

  

  1. (Department of Mathematics & Computational Science, Guangdong University of Business Studies, Guangzhou 510320)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-06-05 Published:2008-06-05

摘要: 为了克服微分进化的局部收敛问题,通过模拟游牧民族的迁徙机制,提出一种迁徙策略,将其与差分进化算法相结合,得到一种迁徙差分进化算法新范式,利用集成技术,发挥各种差分进化算法的优点,提高算法的全局搜索能力。通过生物序列模体识别实验,验证了该算法的有效性。

关键词: 迁徙策略, 模体识别, 差分进化算法, 协同进化

Abstract: In order to solve the problem of local convergence in differential evolution, this paper proposes migration strategy by simulating nomadic migration, and gets a novel migration differential evolution model by merging migration strategy. The algorithm with ensemble technique sufficiently exerts the advantages of different differential evolution, and its global search capability is enhanced badly. The algorithm is used to deal with biological sequence motif detection, and experiments show that it is effective

Key words: migration strategy, motif detection, differential evolution, harmonious evolution

中图分类号: