Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (27): 246-248.DOI: 10.3778/j.issn.1002-8331.2009.27.074

• 工程与应用 • Previous Articles    

Determining molecular formulas of organic compounds by Particle Swarm Optimization algorithm

CHEN Xiao-dong1,ZHANG Yu-min2,XU yue1   

  1. 1.Experimental Center of Testing Science,Jilin University,Changchun 130023,China
    2.College of Chemistry,Jilin University,Changchun 130023,China
  • Received:2008-07-01 Revised:2008-09-12 Online:2009-09-21 Published:2009-09-21
  • Contact: CHEN Xiao-dong

应用微粒群算法确定有机化合物分子式

陈晓东1,张玉敏2,徐 跃1   

  1. 1.吉林大学 测试科学实验中心,长春 130023
    2.吉林大学 化学学院,长春 130023
  • 通讯作者: 陈晓东

Abstract: To avoid the premature problem and the slow convergence of particle swarm optimization algorithm(PSO),an improved particle swarm optimization algorithm(IPSO) is presented to used for determining molecular formulas of organic compounds.On the basic of integer programming and the PSO with contraction factor,the IPSO with mutation probability is proposed to get a good population diversity and to avoid PSO getting into local best result.The algorithm applied to determine molecular formulas of organic compounds is much better than those of PSO and PSO_HPO.

Key words: Particle Swarm Optimization algorithm, integer programming, mutation probability, mass fraction, molecular formulas

摘要: 针对基本微粒群优化算法(PSO)存在容易陷入局部最优和收敛速度慢的缺点,在整数空间使用带收缩因子的微粒群优化算法基础上,提出了一种带变异概率的微粒群优化算法(IPSO),用于提高微粒群的多样性,避免算法陷入局部最优解。实验证明,改进后的微粒群优化算法在防止早熟和加快收敛方面优于基本PSO算法和基本PSO算法加一半微粒随机初始化算法(PSO_HPO算法)。IPSO算法应用到确定有机化合物分子式时,取得了很好的效果。

关键词: 微粒群优化算法, 整数规划, 变异概率, 质量分数, 分子式

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