作　　者： ; ;

机构地区： 广东商学院数学与计算科学学院

出　　处： 《计算机工程与应用》 2007年第3期26-29,共4页

摘　　要： RNA二级结构预测在计算生物学中具有重要意义,针对RNA二级结构预测,提出了一种新的免疫粒子群集成算法,根据个体的浓度和适应值概率,利用免疫机制,在粒子群优化算法中设计了免疫替换算子,有效防止了粒子群优化算法易陷入局部最优的缺陷;通过集成技术,充分发挥各种粒子群优化算法的优点,实现协同演化,提高了算法的全局搜索能力。最后用免疫粒子群集成算法去预测RNA二级结构,实验证明了算法的有效性。 The prediction of RNA secondary structure has important significance in computational biology,in order to predict RNA secondary structure,a new immune particle swarm optimization ensemble has been presented.The local extremum problem of PSO has been solved by designing immune substitution operator,which is determined by fitness and density probability of individual based on immune mechanism.The algorithm with ensemble technique not only sufficiently exerts the advantages of different particle swarm optimization and carries out harmonious evolution ,but also the global search capability of the algorithm has been enhanced badly.Finally,an algorithm based on immune particle swarm optimization ensemble has been used to predict RNA secondary structure;the experiments show that the algorithm is effective.

关 键 词： 二级结构 计算生物学 粒子群优化算法 免疫机理 协同进化

领　　域： [自动化与计算机技术] [自动化与计算机技术]