Result shows that the improved PSO is brief and effective, and enhances the reconnaissance efficiency of the UAVs greatly.
结果表明，该算法简单有效，在很大程度上提高了无人机的侦察效率。
The simulation results show that the improved PSO algorithm can solve the high-dimensional numerical optimization problem effectively.
实验结果表明该改进微粒群算法可以有效地解决高维数值优化问题。
And, in FNN weight training, improved PSO in the convergence rate and the ability to jump out to local optimum algorithm is better than BP.
且改进的粒子群算法在模糊神经网络权值的训练中收敛速度和跳出局部最优的能力都要比BP算法更优。
Application examples show that it is feasible to apply the improved PSO to the weight solution of power load combination forecasting model.
通过应用实例证明，将改进的粒子群优化算法应用到电力负荷组合预测模型的权重求解是可行的。
The results indicate the validity of improved PSO methods in the back analysis of the mechanical parameters of concrete face rock-fill dam.
计算结果表明，微粒群算法具有概念简单、容易实现、计算速度快等优点，适合应用于面板堆石坝坝料参数反演分析。
The structure of multi-layer feedback forward neural network is optimized by improved PSO. Learning quality and training speed of the neural network are improved.
提出的自适应粒子群优化算法，用于优化多层前馈神经网络的拓扑结构，提高了神经网络的学习质量和速度。
An improved particle swarm optimization (PSO) algorithm was designed. And a weighted ITAE index of turbine speed error was taken as the fitness function of the improved PSO algorithm.
提出了一种新的改进的粒子群优化算法，并以水轮机转速偏差的加权ITAE指标作为改进粒子群优化算法的适应度函数。
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)。
The improved PSO is then applied to optimal design of disk brake in order to minimize the brake time under the conditions of geometry constrain, intensity constrain and temperature constrain.
应用此方法，以制动时间最短为目标，在几何约束、强度约束、温度约束等条件下，对盘式制动器的主要设计参数进行了优化设计。
The improved PSO algorithm is tested in two models, to show the effects of improvement and its ability in solving the inverse time overcurrent relay coordination problem when DG units are connected.
通过对两个算例的分析可看到改进算法的效果以及粒子群算法解决分布式电源并网情况下反时限过流保护整定问题的能力。
The improved PSO algorithm is tested in two models, to show the effects of improvement and its ability in solving the inverse time overcurrent relay coordination problem when DG units are connected.
通过对两个算例的分析可看到改进算法的效果以及粒子群算法解决分布式电源并网情况下反时限过流保护整定问题的能力。
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