摘要
根据RNA二级结构预测问题实质和基本粒子群优化算法特性,提出一种离散粒子群优化算法模型.定义该模型中一个可变集合搜索空间,设计了基于此空间粒子群速度与位置更新公式及运算规则.采用局部精英粒子优化策略解决了粒子群算法易陷入局部最优的问题.实验结果表明,该算法在收敛速度和精度上都具有较好的性能.
With the RNA secondary structure prediction and the characteristics of particle swarm optimization, a new model of discrete particle swarm optimization is presented. In the model, searching space of variable set is defined. The operation rules and the update formulae of particle's velocity and location are re-designed on the searching space. A local elitist particle strategy is introduced in order to avoid being trapped in local optima. The experimental results demonstrate the superiority of the proposed model over the other methods in terms of solution quality and convergence rates.
出处
《深圳大学学报(理工版)》
EI
CAS
北大核心
2009年第3期272-277,共6页
Journal of Shenzhen University(Science and Engineering)
基金
国家863高技术研究发展计划资助项目(2007AA01Z423)
重庆市自然科学基金资助项目(2007BB2134)
关键词
离散粒子群优化
RNA二级结构
最小自由能
组合优化
discrete particle swarm optimization
RNA secondary structure
minimum free energy
combinatorialoptimization