CAJ | 학술논문

标准粒子群算法的学习因子是固定值，但是研究发现这种取法却并不合适，会影响到算法的性能。本文通过研究得到以下结论：为了保证粒子群算法搜索到更广阔的空间以及粒子的收敛性，不管是调整单个学习因子还是两个同时调整，学习因子 c1对应的函数都应该先凹后凸，而c2对应的函数应该先凸后凹；绝大多数情况下两个因子一起调整会比只调整一个要好；两种调整策略同样都是c1对应的函数先凹后凸、而 c2对应的函数先凸后凹的情况时，非对称性调整优于对称性调整。
표준입자군산법적학습인자시고정치，단시연구발현저충취법각병불합괄，회영향도산법적성능。본문통과연구득도이하결론：위료보증입자군산법수색도경엄활적공간이급입자적수렴성，불관시조정단개학습인자환시량개동시조정，학습인자 c1대응적함수도응해선요후철，이c2대응적함수응해선철후요；절대다수정황하량개인자일기조정회비지조정일개요호；량충조정책략동양도시c1대응적함수선요후철、이 c2대응적함수선철후요적정황시，비대칭성조정우우대칭성조정。
The acceleration coefficients of standard PSO are fixed numbers ,but the research showed it is not appropriate because the performance of this algorithm would be destroyed . Three conclusions had been drawn in this paper :To assure the wider search range and the convergence of the particles ,w hether you changed only one acceleration coefficient or both acceleration coefficients ,c1 should begin with concave and end with convex and c2 was con‐versely ;Generally speaking ,PSO performed better w hen changed both acceleration coeffi‐cients at the same time than only changed one of them ;Non‐symmetric adjustment was bet‐ter than symmetric adjustment when two strategies both were the first circumstance .