Abstract: Based on SetPSO algorithm, an improved immune particle swarm optimization algorithm is designed for the RNA secondary prediction problem. The SetPSO algorithm is easy to fall into local optimum. According to the characteristics of RNA folding, an immune memory operator is used to tackle this shortage and increase the diversity of particle swarm. Simulation results show that the improved algorithm can get better prediction accuracy in shorter time.

Key words: Ribonucleic Acid（RNA） secondary structure prediction, particle swarm optimization, immune memory operator

摘要： 针对RNA二级结构预测问题，在SetPSO算法的基础上提出了一种改进的免疫粒子群优化算法，根据RNA折叠的特点，启用免疫记忆算子增加粒子群多样性，有效防止了原方法易陷入局部最优的缺陷。仿真结果表明改进算法能在更短的时间内达到更高的预测精度。

关键词: 核糖核酸（RNA）二级结构预测, 粒子群优化, 免疫记忆算子