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粒子群优化算法及其应用 被引量：2

The Algorithm of Particle Swarm Optimization and Applications
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摘要 介绍了粒子群优化算法及该算法的优越性,并与遗传优化算法进行了比较;针对经典粒子群算法存在的不足,介绍了一个改进的动态改变惯性权的自适应粒子群算法;最后,以神经网络为例给出了粒子群优化算法的应用. The algorithm of particle swarm optimization and it＇s advantages are introduced. Performance between genetic algorithm and particle swarm otion algorithm are compared. A perfected adaptive particle swarm algorithm with dynamically changing inertia weight is introduced due to the classical PSO with some deficiencies. An actual example about ANN is gived.
作者 李丙春
机构地区 喀什师范学院网络中心
出处 《喀什师范学院学报》 2006年第3期66-68,共3页 Journal of Kashgar Teachers College
关键词 粒子群优化算法 自适应 神经网络 Particle Swarm Optimization Self- adaptive Neural Network
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献5

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二级参考文献6

  • 1Eberhart R C,Kennedy J. A new optimizer using particle swarm theory [A]. Proceedings of the Sixth International Symposium on Micro Machine and Human Science [C]. Piscataway, USA: IEEE Service Center, 1995. 39-43.
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共引文献137

同被引文献20

  • 1邹毅,朱晓萍,霍龙,赵连学.一种改进的粒子群优化算法及其应用[J].沈阳工程学院学报（自然科学版）,2006,2(3):283-286. 被引量：5
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  • 8Taylor R H. A perspective on medical robotics[J]. Proceedings of the IEEE, 2006, 94(9): 1652-1664.
  • 9Sun L W, Yeung C K. Port placement and pose selection of the da Vinci surgical system for collision-free intervention based on performance optimization[C]//IEEE/RSJ International Con- ference on Intelligent Robots and Systems. Piscataway, USA: IEEE, 2007: 1951-1956.
  • 10Trejos A L, Patel R V. Port placement for endoscopic cardiac.surgery based on robot dexterity optimization[C]//1EEE Inter- national Conference on Robotics and Automation. Piscataway, USA: IEEE, 2005: 912-917.

引证文献2

二级引证文献10

喀什师范学院学报
2006年 第3期

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