pso

Particls swarm optimization ( PSO ) algorithm is a stochastic global optimization method.

粒子群优化算法是一种全局随机优化算法.

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PSO and Its Application to Relevance Feedback in Image Retrieval.

粒子群优化算法及其在图像检索中相关反馈上的应用.

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Particle Swarm Optimization ( PSO ) for the TSP complete source code, has been tested.

粒子群优化 ( PSO ) 的完整的TSP的源代码, 已经过测试.

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Experiment results have shown that PSO and ANN are effective in Voiceprint Recognition.

实验结果表明，PSO和ANN结合模型在声纹识别上具有很好的识别效果，是比较有效的识别方法。

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PSO schedule algorithm for DAG task model

DAG任务模型的粒子群优化调度算法

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Improved PSO and its application in crystallizer liquid level control system

改进的PSO及其在结晶器液位控制中的应用

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The contradiction the global exploration and convergence speed particle swarm optimization ( PSO ) algorithm is analyzed.

分析了基本粒子群算法 ( PSO ) 全局搜索能力与收敛速度的矛盾,提出了粒子群相似度的概念.

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The Deployment and Retrieval Control of the Tethered Satellite Based on the PSO Algorithm

基于粒子群算法的绳系卫星展开与回收控制

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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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PSO being iterations random algorithm does better in fast constringency and finding the optimization solution with biggish probability.

PSO算法本质上属于迭代的随机搜索算法，其主要优点在于收敛速度快、能以较大的概率找到优化问题的全局最优解等。

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A method to evaluate spatial straightness errors adopting particle swarm optimization ( PSO ) is proposed.

摘要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.

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Based on the idea specialization and cooperation, an adaptive Particle Swarm Optimization ( PSO ) algorithm is proposed.

基于粒子分工与合作的思想, 提出一种自适应粒子群优化 ( PSO ) 算法.

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While the population size exceed presetting threshold, the population size decrease to original state. Then, to solve discrete optimization problem, PSO algorithm is modified to discrete one.

当种群规模超过预先设置好的阈值时，将种群规模降为初始状态。（2）为求解聚类问题，将PSO算法修改为离散化PSO。

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Therefore, we recommend using PSO to solve the optimal solution of the problem model.

因此我们建议使用PSO演 算法来解决模式的最佳解问题.

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A cylindricity evaluation approach based on the Particle Swarm Optimization ( PSO ) was proposed.

提出了将粒子群优化算法用于圆柱 度误差 评定的设想.

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PSO-BP method was presented based on the testing of the battery performance, which used the battery voltage, charge-discharge rate and temperature as the input features parameters of neural network to estimate the battery SOC.

在电池性能测试基础上，提出采用PSO-BP方法，利用电池电压、充放电倍率和温度作为神经网络输入特征参数，估算电池SOC。

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A parallel PSO was studied based on the parallel model with controller that is coarse-grain parallel.

现提出了一种基于带控制器并行结构模型的并行微粒群算法,它是一种粗粒度的并行.

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On consideration of the search characteristics of particle swarmabr. PSO , penalty function is assigned dynamically.

针对改进粒子群算法的搜索特点,动态调节罚函数.

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This PSO approach provides a new way to solve constrained problems for the practical applications.

该粒子群算法为实际应用中约束优化问题的求解提供了新的途径.

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Application of RBF-PSO in Nonlinear Calibration for Thermocouple Sensor

RBF-PSO在N型热电偶非线性校正中的应用

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Non-equidistant distributed PSO method based on the rate of change of barrier is proposed to enhance the adaptability to the environment.

提出了基于障碍物变化率的非等间距分布的PSO路径规划方法，增强了PSO对环境的适应性。

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Research on PSO Algorithm of Task Allocation in Wireless Sensor Network

无线传感器网络任务分配的粒子群优化算法

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The improvement nearest neighbor algorithm and cheapest insertion algorithm are combined with PSO as the post-optimization-procedure.

将改进的最邻近插入法和最廉价插入法作为后优化过程与粒子群优化算法结合求解该问题.

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The improved discrete binary quantum particle swarm optimization ( PSO) algorithm and Fisher classifier which constructed based on kernels is used to do feature selection.

再用改进的离散二进制量子粒子群算法与基于核的Fisher分类器相结合进行特征选择。

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Meanwhile , chaos mutation adopted in order to increase the diversity of particles of PSO.

为有效保证PSO算法的粒子多样性, 在迭代过程中加入混沌变异.

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PSO algorithm is a type of full-scale random algorithm of optimization.

PSO算法是一种全局随机优化算法。

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This paper presents a new polygonal approximation approach based on the particle swarm optimization ( PSO ) algorithm.

本文提出了一种新的基于粒子群优化算法 ( PSO ) 的多边形近似方法.

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The two concepts of deviation threshold and collision strength are used to adjust the exploration and exploitation ability of Catfish-PSO algorithm in order to optimize its performance.

算法中引入偏差阈值和冲撞力度两个概念，来调整种群的探测和开发能力，达到优化算法性能的目的。

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Aiming to solve out the pre-mature convergence phenomenon, the chaos mutation is introduced into PSO for improving global optimal ability.

混沌变异机制引入到PSO算法中，克服了进化过程中出现的早熟收敛现象，改进了PSO算法的全局寻优能力；

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An improved PSO algorithm was presented and applied to optimal the PID parameters of electromotor.

为此,提出一种改进的PSO优化算法,并将该算法应用于电机控制系统的PID参数优化设计.

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