A method based on improved binary particle swarm optimization (PSO) is proposed for distribution network reconfiguration with the objective of load balancing.
提出了基于改进的二进制粒子群优化算法、以均衡负荷为目标的配电网重构方法。
Second, an Enhanced Phase Locked Loop (EPLL) control strategy based on improved Adaptive Notch Filtering (ANF) is proposed, controller parameters are optimized using BF-PSO algorithm.
其次，提出了一种基于改进型ANF的三相EPLL控制策略，并用BF-PSO算法对控制器参数进行优化设计。
As Particle Swarm Optimization (PSO) may easily get trapped in a local optimum, an improved PSO based on adaptive dynamic neighborhood and comprehensive learning named ADPSO was proposed.
为了克服粒子群算法在求解多峰函数时极易陷入局部最优解的缺陷，提出一种基于自适应动态邻居广义学习的改进粒子群算法(ADPSO)。
It USES the dynamic scale-free like network as the particle's optimization neighborhood. It proposes an improved PSO algorithm based on variety inertia weight and dynamic neighborhood.
将有向动态类无标度网作为粒子寻优邻域，提出一种基于变惯性权重及动态邻域的改进P SO算法。
It USES the dynamic scale-free like network as the particle's optimization neighborhood. It proposes an improved PSO algorithm based on variety inertia weight and dynamic neighborhood.
将有向动态类无标度网作为粒子寻优邻域，提出一种基于变惯性权重及动态邻域的改进P SO算法。
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