列举出出两篇最近两年发表的与粒子群算法有关的sci论文

"A hybrid particle swarm optimization algorithm with adaptive learning rate for global optimization" (2020) - This paper proposes a hybrid particle swarm optimization algorithm that incorporates an adaptive learning rate mechanism to improve convergence speed and accuracy. The algorithm is tested on benchmark functions and real-world engineering problems, demonstrating its effectiveness compared to other state-of-the-art algorithms.

"Particle swarm optimization-based feature selection for high-dimensional microarray data" (2019) - This paper presents a particle swarm optimization-based feature selection method for analyzing high-dimensional microarray data. The method is applied to several cancer datasets, demonstrating its ability to effectively identify relevant genes and improve classification accuracy compared to other feature selection methods