particle swarm

英 [ˈpɑːtɪkl swɔːm] 美 [ˈpɑːrtɪkl swɔːrm]

颗粒群

化学



双语例句

  1. A multi-objective particle swarm optimization algorithm based on online elite archiving is proposed.
    提出一种基于在线归档技术的新型多目标粒子群优化算法。
  2. Particle swarm optimization is described and analyzed; and it is applied to calibrate Xin'anjiang model.
    对粒子群算法进行了详细描述和分析,并将其应用于新安江模型的参数优选中。
  3. Research and Application of Particle Swarm Optimizer in Structural Optimization
    结构优化中粒子群算法的研究与应用
  4. The reasons of premature convergence of Particle Swarm Optimization ( PSO) Algorithm were analyzed.
    分析了粒子群优化(PSO)算法易于发生早熟收敛的原因。
  5. Classification is one tasks of data mining, using particle swarm optimization in classification especially classification rule extraction.
    分类是数据挖掘研究的主要内容之一,将微粒群算法应用于分类问题,进行分类规则的提取。
  6. A new method of public traffic line network optimization is presented by particle swarm algorithm.
    针对公交线网优化问题,利用粒子群算法进行了研究。
  7. In this paper, a modified particle swarm optimization method is proposed.
    提出了改进的粒子群优化算法。
  8. Mixture control of chaotic system using particle swarm optimization algorithms and OGY method
    基于粒子群算法和OGY方法的混沌系统混合控制
  9. New clustering algorithm based on Particle Swarm Optimization and simulated annealing
    一种新的基于粒子群和模拟退火的聚类算法
  10. A method to evaluate spatial straightness errors adopting particle swarm optimization ( PSO) is proposed.
    提出了一种满足最小区域法的空间直线度误差评价的新方法一粒子群算法。
  11. A new hybrid clustering algorithm based on particle swarm optimization and FCM algorithm is proposed.
    提出了一种基于模糊C均值算法和粒子群算法的混合算法。
  12. Particle swarm algorithm was an optimized algorithm based on swarm intelligence.
    粒子群算法是一类基于群智能的随机优化算法。
  13. Particle Swarm Optimization ( PSO) algorithm has existed premature convergence for multimodal search problems.
    粒子群优化(PSO)算法对于多峰搜索问题一直存在早熟收敛问题。
  14. Outlier Mining Algorithm Based on Particle Swarm Optimization and Subspace
    基于微粒群和子空间的离群数据挖掘算法研究
  15. Hybrid particle swarm optimization algorithm merging simulated annealing and chaos
    融合模拟退火和混沌的混合粒子群算法
  16. Data Mining Method Research Based on Rough Set and Particle Swarm Optimization
    基于粗糙集和粒子群的数据挖掘方法研究
  17. Research of particle swarm optimization algorithm comparison with back-propagation algorithm and genetic algorithm
    粒子群优化算法与BP算法和遗传算法的比较研究
  18. A structural damage identification method based on the support vector machine and the particle swarm algorithm was proposed.
    为了有效地进行结构的损伤识别,提出了一种基于支持向量机和粒子群算法的结构损伤识别方法。
  19. A particle swarm optimization algorithm for low voltage apparatus blanking part layout optimization was presented.
    提出了一种粒子群算法的低压电器冲裁件排样优化问题的求解方法。
  20. Optimization algorithm based on simulated annealing and cultural-based particle swarm
    基于模拟退火和文化粒子群的优化算法
  21. This paper describes a niching multi-objective Particle Swarm Optimization ( PSO) algorithm.
    提出一种小生境多目标粒子群优化算法。
  22. A particle swarm optimization algorithm source code, this is a VB source languages, it is practical.
    一种粒子群优化算法源程序,这是一个VB语言编制的源程序,很实用。
  23. This paper introduces a bounded mutation operator into Quantum-behaved Particle Swarm Optimization ( QPSO) algorithm and proposes QPSOB.
    将边界变异操作引入到量子粒子群优化算法中,提出基于边界变异的量子粒子群优化算法(QPSO)B。
  24. Space division particle swarm optimization is proposed to solve the high-dimensional numerical optimization problem in this paper.
    提出了一种适用于高维数值优化问题的空间分割微粒群算法。
  25. A novel automatic registration method based on contour feature points and particle swarm optimization ( PSO) is presented.
    提出了一种基于轮廓特征点及利用PSO(粒子群优化)求解多模态医学图像自动配准新方法。
  26. PSO algorithm; chaotic particle swarm optimization algorithm; constrained optimization; penalty function;
    PSO算法;混沌粒子群算法;约束优化;惩罚函数;
  27. Particle Swarm Algorithm's Research and Application in Clustering and QoS Multicast Routing
    微粒群算法在聚类分析及QoS组播路由中的应用研究
  28. A new self-adaptive particle swarm optimization ( AMPSO) is presented.
    提出了一种新的自适应粒子群优化算法(AMPSO)。
  29. Aimed at PSO's defect of prematurity, an improved particle swarm optimization ( IPSO) is presented.
    针对粒子群算法本身存在早熟的不足,提出了一种改进的粒子群优化算法(IPSO)。
  30. So An optimal selection approach of SVR parameters was put forward based on improved particle swarm optimization algorithm.
    因此提出了基于改进粒子群算法的SVR参数优化选择方法。