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周期性扰动的微粒群算法
引用本文:于来行,乔蕊.周期性扰动的微粒群算法[J].计算机系统应用,2011,20(6):203-206.
作者姓名:于来行  乔蕊
作者单位:周口师范学院计算机科学系,周口,466001
基金项目:周口师范学院青年科研基金
摘    要:微粒群算法中微粒有保持自身状态的特性,如何改变其状态对微粒位置和速度的调整有较大的影响,本文给出一种周期性随机扰动的自适应改变微粒速度的方法.当微粒要进行下一次运动时,总体采用非线性下降的惯性权重选择方法,并且在其中加入周期性随机扰动策略,使算法既能得到较快的收敛速度,又不至于陷入局部极值.将此方法应用于对几个标准函数...

关 键 词:微粒群算法  自适应  随机扰动  惯性权重
收稿时间:2010/10/11 0:00:00
修稿时间:2010/11/17 0:00:00

Particle Swarm Algorithm of Periodic Random Disturbance
YU Lai-Hang and QIAO Rui.Particle Swarm Algorithm of Periodic Random Disturbance[J].Computer Systems& Applications,2011,20(6):203-206.
Authors:YU Lai-Hang and QIAO Rui
Affiliation:YU Lai-Hang,QIAO Rui (Department of Computer Science,Zhoukou Normal University,Zhoukou 466001,China)
Abstract:Particle, among swam algorithm, is apt to keep its own state. While how to change its state has great influence on the position and the adjustment of the velocity. In this paper presents a new method-an adaptive particle swarm algorithm of periodic random disturbance strategy. And the nonlinear declination as well as Self-adapting inertia improved in the process of particles moving. Better results can be obtained by the new method compared with the former ones and which only adopts linear decline in the oarticle swarm algorithrn.
Keywords:particle swarm optimization  adaptive  random disturbance  self-adapting inertia  
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