CAJ | 학술논문

研究了带压缩因子的粒子群算法，通过配置最优参数以及控制收敛速度来改进粒子群聚类算法，并利用它对 IRIS 数据集和 WINE 数据集进行测试。实验结果表明，改进后的算法能控制粒子群的更新速度，并有效改进粒子群算法的准确率和全局收敛性。
연구료대압축인자적입자군산법，통과배치최우삼수이급공제수렴속도래개진입자군취류산법，병이용타대 IRIS 수거집화 WINE 수거집진행측시。실험결과표명，개진후적산법능공제입자군적경신속도，병유효개진입자군산법적준학솔화전국수렴성。
Particle swarm optimization with compression factor is researched.By configuring optimal parameters and controlling the convergence rate,the particle clustering algorithm is improved by which the IRIS data set and WINE set are tested.The result shows that the improved algorithm controls the updated rate of particle swarm,and effectively improves the accuracy and the whole convergence of particle swarm optimization.