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[matlab] Pso DL : 0: 模拟一群鸟捕食的情景，从而达到优化目标函数的目的，这就是粒子群算法！起初在可行的空间中随机的产生一群粒子，然后让每个粒子开始在虚拟的空间中向四面八方飞翔，并且每个粒子都记下他们飞过的适应值（也就是目标优化函数）最高的点，而且整个粒子群有一个最高适应值个体，这样，粒子在飞翔的时候尽量朝向自己曾飞过的最好的点和集体的最好的点。最后达到收敛到近似最优点的目的。 -Simulation of a group of birds preying on the scene, so as to achieve the purpose of optimizing the objective function, that is, PSO! At first, where feasible, have a space in a group of random particles, and then let the beginning of each particle in a virtual space to fly in all directions, and each particle they have in mind over the fitness value (that is objective optimization function) the highest point , and the whole particle swarm adaptation has a maximum value of the individual, so that particles in the fly when he had flown as far as possible towards the best point and collective best point. Finally reaching the merits of convergence to approximate most purposes.
Date : 2025-12-26 Size : 4kb User : chen
[matlab] pso DL : 0: 基于多线程机制的，利用Matlab编写，粒子群优化算法。目标变量采用归一化处理，适用于所有的优化函数。优化函数自定义为fitness(x)。-Based on multi-threading mechanism, the use of Matlab to prepare, particle swarm optimization algorithm. Target variables using normalized treatment applies to all of the optimization function. Since the optimization function is defined as fitness (x).
Date : 2025-12-26 Size : 1kb User : lys
[matlab] pso DL : 0: 个程序就是最基本的粒子群优化算法程序，用Matlab实现，非常简单。是主函数的源程序，优化函数则以m文件的形式放在fitness.m里面，对不同的优化函数只要修改fitness.m就可以了通用性很强。-Procedures is the most basic particle swarm optimization procedures, using Matlab realize, is very simple. Is the main function of the source, optimizing the function with m the form of documents on fitness.m inside, optimized for different functions as long as the modifications can fitness.m highly generic.
Date : 2025-12-26 Size : 1kb User : 牛牛
[matlab] PSO(matlab) DL : 0: PSO算法，通用性较强，只要换一下fitness就可以了-PSO algorithm, universal strong, as long as a change in fitness can be a
Date : 2025-12-26 Size : 1kb User : 曾嘉俊
[matlab] pso DL : 0: Date : 2025-12-26 Size : 1kb User : bread
[matlab] PSO DL : 0: 用粒子群算法优化RBF网络权值，根据适应度值对个体最优和群体最优进行更新-Particle Swarm Optimization with RBF network weights, according to the best fitness value of individuals and groups to update the best
Date : 2025-12-26 Size : 1kb User : 天涯
[matlab] PSO DL : 0: 微粒群优化算法，经典的粒子群优化算法，第一参数是适应值函数，因此方便多次使用-Particle swarm optimization algorithm, the classical particle swarm optimization algorithm, the first parameter is the fitness function, so convenient to use many times
Date : 2025-12-26 Size : 1kb User : BISer
[matlab] PSO DL : 0: PSO对函数进行优化，pso.m为主函数程序,fitness.m为适应度函数，程序以通过调试。-PSO function to optimize the program through the debugger
Date : 2025-12-26 Size : 5kb User : 任超
[matlab] pso DL : 0: 粒子群算法的编码，通过调整种群大小来实现不同范围和精度的搜索，其中的fitness函数需要自行编写-PSO coding, by adjusting the population size to achieve different range and accuracy of search, in which the fitness function needs to write their own
Date : 2025-12-26 Size : 1kb User : david
[matlab] PSO-algorithm- DL : 0: 这个程序就是最基本的粒子群优化算法程序，用Matlab实现。优化函数则以m文件的形式放在fitness.m里面，对不同的优化函数只要修改fitness.m就可以了通用性很强。-This program is the most basic particle swarm optimization procedures, using Matlab to achieve. Optimizing the function with the form of m documents on fitness.m inside, optimized for different functions as long as the modifications can fitness.m very versatile.
Date : 2025-12-26 Size : 1kb User : yu
[matlab] pso DL : 0: 粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO，是近年来发展起来的一种新的进化算法(（Evolu2tionary Algorithm - EA）。PSO 算法属于进化算法的一种，和遗传算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。-Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years ((Evolu2tionary Algorithm- EA) .PSO algorithm is an evolutionary algorithm, and similar genetic algorithm, it is also starting random solutions, through iterative search for the optimal solution, which is also uated by the quality of the fitness solution, but it is much simpler than genetic algorithms rule, it does not have the genetic algorithm cross (Crossover) and variant (Mutation) operation, which by following the current search to find the optimal value to the global optimum. the algorithm for its easy implementation, high accuracy, and fast convergence advantages attracted academic attention, and in solving practical problems demonstrated its superiority.
Date : 2025-12-26 Size : 7kb User : 了了
[matlab] PSO DL : 0: 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 thought of the implementation of the standard particle swarm algorithm according to the particle swarm algorithm (2)- the standard particle swarm algorithm about implementation. Mainly divided into three functions. The first function of particle swarm initialization function InitSwarm (SwarmSize... AdaptFunc), its main function is to initialize particle swarm particle, and set the particle s velocity, position in a certain range. The function of data structure is as follows: ParSwarm record table is the particle s position, speed and the current fitness value, we use W to represent the position, represented speed with a V, to represent the current fitness value with F. Here we assume that the number of particles N, each particle dimension for D.
Date : 2025-12-26 Size : 3kb User : patricia
[matlab] PSO DL : 0: 粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO，是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。-Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm.
Date : 2025-12-26 Size : 2kb User : 艾岳巍
[matlab] pso-bp DL : 0: 粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO，是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。 BP（Back Propagation）神经网络是1986年由Rumelhart和McCelland为首的科学家小组提出，是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法，通过反向传播来不断调整网络的权值和阈值，使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层（input）、隐层(hidden layer)和输出层(output layer)。-Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm. BP (Back Propagation) neural network is a 1986 team of scientists headed by Rumelhart and McC
Date : 2025-12-26 Size : 2kb User : 艾岳巍
[matlab] PSO DL : 0: 用基本粒子群算法来解决优化问题，本程序给出的是测试函数，根据需要可以自行更改适应度函数。-Using particle swarm optimization algorithm to solve the problem, this program is given a test function, you can change the fitness function according to their needs.
Date : 2025-12-26 Size : 2kb User : xushipeng
[matlab] PSO DL : 0: pso算法通过初始化参数，更新每个粒子的速度和位置，计算粒子的适应度值，找到最佳适应值。该代码以图形的形式形象地说明了粒子最佳位置随着迭代次数的变化趋势。-Pso algorithm initializes some parameters, updates the speed and position of each particle, calculates the fitness value of particles, and finds the best fitness. The source code in the form of graphic vividly illustrates the change trend of particle best position as the number of iterations.
Date : 2025-12-26 Size : 2kb User : HENAN
[matlab] PSO DL : 0: pso ，粒子群算法的matlab实现，包含fitness.m和pso.m(Particle swarm optimization)
Date : 2025-12-26 Size : 1kb User : Qoung
[matlab] PSO&GA DL : 0: 本文件对PID参数kp,ki,kd进行寻优，以ITAE作为指标函数。 PSO 文件中有详细的参数设置和寻优过程 GA寻优与PSO寻优作为对比出现 figure1展示了随着迭代次数的变化，适应度函数的收敛情况 figure2展示了kp,ki,kd的迭代情况 ht 文件是用来画图的问题解决思路.pdf 简要介绍了粒子群算法寻优的过程(In this document, the PID parameters KP, Ki, KD are optimized, and ITAE is used as the index function. PSO file has detailed parameter settings and optimization process GA optimization and PSO optimization as a contrast appear Figure1 shows the convergence of fitness function as the number of iterations changes Figure2 shows the iterations of KP, Ki, and KD The HT file is used for drawing The problem solving idea.Pdf briefly introduces the process of particle swarm optimization)
Date : 2025-12-26 Size : 249kb User : 大燕
[matlab] PSO DL : 0: Particle swarm optimization (PSO) is a derivative-free global optimum solver. It is inspired by the surprisingly organized behaviour of large groups of simple animals, such as flocks of birds, schools of fish, or swarms of locusts. The individual creatures, or "particles", in this algorithm are primitive, knowing only four simple things: 1 & 2) their own current location in the search space and fitness value, 3) their previous personal best location, and 4) the overall best location found by all the particles in the "swarm". There are no gradients or Hessians to calculate
Date : 2025-12-26 Size : 35kb User : mahmood
[matlab] pso DL : 0: PSO 算法属于进化算法的一种，和模拟退火算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的"交叉"(Crossover) 和"变异"(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。(The PSO algorithm is a kind of evolutionary algorithm. Similar to the simulated annealing algorithm, it also starts from the random solution and iteratively finds the optimal solution. It also evaluates the quality of the solution through fitness, but it is simpler than the genetic algorithm rules. It does not have the "Crossover" and "Mutation" operations of the genetic algorithm. It seeks the global optimum by following the current searched optimal value. This kind of algorithm has attracted much attention from the academic community because of its advantages of easy implementation, high precision and fast convergence. It also shows its superiority in solving practical problems. Particle swarm algorithm is a parallel algorithm.)
Date : 2025-12-26 Size : 1kb User : cinderella345

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