1) Hybrid particle swarm optimization
混合粒子群算法
1.
A hybrid particle swarm optimization algorithm was applied in each time interval to carry on the static reconfiguration and obtain a solution set.
将一天分为多个时段,每一时段由一个工作代理负责,利用混合粒子群算法进行静态重构,求得一个解集,并通过相邻代理间的相互学习,对解集进行补充和完善。
2.
A hybrid particle swarm optimization (HPSO.
把灾变理论、混沌优化思想和基本粒子群算法结合起来,形成一种混合粒子群算法。
3.
The hybrid particle swarm optimization, which refines and practices in heuristic algorithm, is a good practice in the process of optimization problems.
由启发式算法中提炼和实践而来的混合粒子群算法在求解的过程中通过对问题在解空间的多点并行搜索,以较大的概率收敛于全局最优解,可以达到优化解集的目的,在优化问题的结果过程中得到良好的实践。
2) hybrid PSO
混合粒子群算法
1.
As a test case,Job Shop illustrates that the new hybrid PSO is feasi.
用Job Shop问题作为测试基准,仿真试验显示混合粒子群算法是可行和有效的。
2.
Hybrid PSO for Solving Modular Product Configuration Optimization Problem;
采用遗传算法的交叉与变异策略和模拟退火算法的Metropolis准则改进粒子群算法,将形成的混合粒子群算法作为产品优化配置的求解方法。
3) hybrid particle swarm algorithm
混合粒子群算法
1.
In order to avoid a great deal of computation and non-identifiable problem possibly presented in the traditional identification method,the hybrid particle swarm algorithm with gradient acceleration is applied to identify.
将基于满意聚类的Takagi-Sugeno建模方法和机理分析方法结合起来解决这些问题,并采用带有梯度加速的混合粒子群算法进行辨识,来解决运算量大和可能出现不可辨识的情况。
4) HPSO
混合粒子群算法
1.
A novel approach for microwave imaging of the perfectly conducting objects in free space using hybrid particle swarm optimization(HPSO) is put forward.
提出了一种能同时重构多个导体目标外形的新方法—混合粒子群算法,利用快速非均匀平面波算法加速求解电磁散射问题,以测量的散射场和计算散射场偏差作为目标函数,将待优化变量设置为目标的截面轮廓近似多边形的矢径参数,通过混合粒子群算法对待优化变量进行优化,使目标函数达到最小值来对自由空间中的散射体进行电磁成像。
5) hybrid particle swarm optimization algorithm
混合粒子群算法
1.
The simulation experiment shows that adopting the hybrid particle swarm optimization algorithm can efficiently solve this type of linear equation systems.
为此,提出了一种混合粒子群算法。
6) PSO-ACO
粒子群-蚁群混合算法
1.
The traditional BP neural network is easy to plunge into local extremum and has a low searching speed,so the swarm intelligence algorithm is used to optimize BP neural network to recognize the speed,and the PSO-ACO hybrid algorithm of the swarm intelligence is used.
传统BP神经网络容易陷入局部极值、寻优速度慢,所以本文用一种群集智能优化算法来优化BP神经网络进行速度辨识,所采用的群集智能算法是粒子群-蚁群混合算法,以此神经网络进行速度辨识。
补充资料：WZ型无重力粒子混合机
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条