搜索资源列表
Discrete_PSO_TSP_C
- 离散粒子群算法(Discrete PSO)C语言源代码。 附带有利用D-PSO解决旅行商问题(TSP)的代码可作为使用时的Demo参考-discrete particle swarm algorithm (Discrete PSO) C language source code. Incidental use of a D-PSO solve the traveling salesman problem (TSP) code can be used as a reference when t
s-hanshu
- PID控制器的参数自适应,需要整定P,I ,D, 此S函数用的是固定步长,并用后向差分离散化。其中Tsa是Simulink的仿真一个周期的时间。在对图 7所示单闭环调速控制系统的动态结构图,在有自适应控制情况下,进行基于PSO算法的PID参数整定时,这个函数也会用到。
测试PSO算法的新的组合测试函数
- Novel Composition Test Functions for Numerical Global Optimization func_test.m is the main program, a basic PSO algorithm PSO_func.m is attached. SIS_novel_func.m is the function program,including six composition functions f=SIS_novel_func(x,f
BasedonprincipalcomponentanalysisoftheFaceRecognit
- 在特征提取阶段,研究了PCA, 2DPCA, (2D) 2PCA, DiagPCA, DiagPCA-F-2DPCA等多 种方法。不同于基于图象向量的PCA特征提取,由于2DPCA, (2D) ZPCA, DiagPCA和 DiagPCA-I-2DPCA的特征提取都直接基于图象矩阵,计算量小,所以特征的提取速度明 显高于PCA方法。-In the feature extraction stage, the study of the PCA, 2DPCA, (2D) 2PCA,
pso
- pso-matlab7.0例子pso(alfaB,yB,alfaN,HBB,HBN,yN,d)-pso-matlab7.0pso(alfaB,yB,alfaN,HBB,HBN,yN,d)
PSO_base_RBF
- PSO的RBFNN优化程序 算法步骤 1.样本数据归一化处理,即将输入输出归一化到[-1,1]区间; 2.确定RBF网络的中心和宽度; 3.以拟合误差的均方根作为性能指标,使用PSO算法优化RBF网络输出层到隐层的连接权值矩阵-PSO-RBFNN algorithm optimization procedures Step 1. Sample data normalization treatment, about input and output normalized to [-
pospdflw
- 这是一个粒子群优化算法的博士毕业论文,适合做毕设,希望对大家有用-This is a PSO Ph.D. thesis, suitable for complete set, we want to be useful
PSO--Overview_v2
- L’apparition des algorithmes évolutionistes à fait l’effet d’une bombe dans les domaines de la résolution de problèmes complexes, et spécialement dans l’optimisation de fonction avec contraintes. L’optimisation par essaim de particules se présent
pso
- 子群优化算法中,粒子群由多个粒子组成,每个粒子的位置代表优化问题在D维搜索空间中潜在的解。根据各自的位置,每个粒子用一个速度来决定其飞行的方向和距离,然后通过优化函数计算出一个适应度函数值(fitness)。-Subgroup of particle swarm optimization algorithm is composed by a number of particles, each particle' s position represents to optimize the p
PSO
- 经典粒子群算法,经过多次优化,演示出图, 待优化的目标函数:N 粒子数目:N 惯性权重:w 学习因子:c1,c2 最大迭代次数:M 问题的维数:D 目标函数取最小值时自变量值:xm 目标函数的最小值:fv-Classical particle swarm algorithm, optimized for many times, demonstrates plotting objective function to be optimized: N of
04470122.rar
- This paper proposes a novel and computationally efficient global I< optimization method based on swarm ntelligence for locating ti nodes in a WSN environment. The mean squared range error of a all neighbouring anchor nodes is taken as the obj
LNCPSO
- 希望给辛苦科研的人带来一点点帮助--学习因子可以变化的PSO算法,不再是c1=c2=2,粒子进化更加灵活,下面是学习因子同步变化的pso,调用形式为[xm,fv]=LNCPSO(fitness,N,cmax,cmin,w,M,D)-People who want to work hard to bring a little bit of research to help- learning factor can vary PSO algorithm is no longer c1 = c2 =
tunning-PID-use-PSO
- 用pso算法优化PID参数,程序中只是对P和D的参数进行了优化-PID parameter optimization using pso algorithm, the program only the P and D parameters were optimized.
PSO_0.3-1.bin
- This document introduces the Particle Swarm Optimization (PSO) in Scilab. The PSO method, published by Kennedy and Eberhart in 1995, is based on a population of points at first stochastically deployed on a search field. Each member
PSO-0.3-1-src
- This document introduces the Particle Swarm Optimization (PSO) in Scilab. The PSO method, published by Kennedy and Eberhart in 1995, is based on a population of points at first stochastically deployed on a search field. Each member
PSO
- 标准粒子群算法的实现思想基本按照粒子群算法(2) 标准的粒子群算法的讲述实现。主要分为3个函数。第一个函数为粒子群初始化函数 InitSwarm(SwarmSize......AdaptFunc)其主要作用是初始化粒子群的粒子,并设定粒子的速度、位置在一定的范围内。本函数所采用的数据结构如下所示: 表ParSwarm记录的是粒子的位置、速度与当前的适应度值,我们用W来表示位置,用V来代表速度,用F来代表当前的适应度值。在这里我们假设粒子个数为N,每个粒子的维数为D。-His though
PSO
- 实现基于PSO的三维图形的极值计算,并显示中间的搜索过程。-Implementation is based on PSO to calculate the extremum of 3 d graphics and display in the middle of the search process.
qhbiekrn
- 基于分段非线性权重值的Pso算法,有PMUSIC 校正前和校正后的比较,旋转机械二维全息谱计算,加入重复控制,DC-DC部分采用定功率单环控制,LDPC码的完整的编译码。- Based on piecewise nonlinear weight value Pso algorithm, A relatively before correction and after correction PMUSIC, Rotating machinery 2-d holographic spectrum ca
sietun
- 基于K均值的PSO聚类算法,D-S证据理论数据融合,有借鉴意义哦。- K-means clustering algorithm based on the PSO, D-S evidence theory data fusion, There are reference Oh.
PSO-rbf-kmeans
- pso rbf k-means simulik with matlab(programme d'un pso en hybride avec un rbf)