Search - pso-fitness

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[AI-NN-PR] thecontrollingofpidinpsoo DL : 0: 基本粒子群优化算法Matlab源程序,其中的fitness函数可根据自己需要更改。-Elementary particle swarm optimization algorithm Matlab source code, in which the fitness function may need to change according to their own.
Date : 2025-12-26 Size : 4kb User : 徐楠
[AI-NN-PR] pso.code DL : 0: 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。-pso code
Date : 2025-12-26 Size : 1kb User : 余超
[AI-NN-PR] pso-down DL : 0: 用python语言编写的粒子群优化算法，内有多种适应度函数可供选择-Python language used particle swarm optimization algorithm, there are a variety of alternative fitness function
Date : 2025-12-26 Size : 3kb User : 海廷
[AI-NN-PR] PSO DL : 0: 一个PSO的源代码,步骤为先计算原始种群的适应度,及初始化，再迭代，计算适应度。-The source code of a PSO, the steps for the first calculation of the fitness of the original population, and initialization, and then iterate to calculate the fitness.
Date : 2025-12-26 Size : 2kb User : 图图
[AI-NN-PR] particle-swarm-algorithm---matlab DL : 0: 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-PSO algorithm is an evolutionary algorithm, and genetic algorithm is similar, it is starting from a random solution, by iteration to find the optimal solution, it is also to evaluate the fitness of the solution by the quality, but it is much simpler than the rules of the genetic algorithm, It is not genetic algorithms " cross" (Crossover) and " variant" (Mutation) operations, which by following the optimal value of the current search to find the global optimum
Date : 2025-12-26 Size : 20kb User : shitou
[AI-NN-PR] PSO_introduction DL : 0: 这是关于粒子群算法的一篇综述论文，说明了PSO算法的原理，及其算法流程！-PSO is a population-based stochastic optimization technique inspired by social behavior of bird flocking or fish schooling. All of particles have fitness values which are evaluated by the fitness function to be optimized, and have velocities which direct the flying of the particles.
Date : 2025-12-26 Size : 312kb User : wanghong
[AI-NN-PR] test DL : 0: 引入能直接处理连续型数据的邻域粗糙集约简模型，给出一种基于邻域粗糙集模型和粒子群优化的特征选择算法。仿真实验结果表明该算法可以选择较少的特征，改善分类的能力。-employs the neighborhood rough set reduction model which can process the numerical features directly without discretization. Then the particle fitness function in particle swarm optimization (PSO) algorithm is built based on that model. Finally, a novel feature selection algorithm based on particle swarm optimization and neighborhood rough set reduction model is proposed. Experimental results prove that the new algorithm improves classification ability with fewer features selected.
Date : 2025-12-26 Size : 16kb User : 伍洁
[AI-NN-PR] constrain-opt DL : 0: 针对工程优化设计问题,提出了基于混沌粒子群算法的工程约束优化问题求解方法。CPSO算法利用混沌搜索的全局遍历性、随机性和规律性等特点, 引导粒子在全局范围内搜索, 从而克服了传统粒子群算法早熟收敛的缺点。该算法以种群适应度方差作为粒子群优化算法早熟收敛的判据, 并用惩罚函数法处理违法约束的粒子, 当基本粒子群算法陷入早熟时, 随机选择粒子群中的部分粒子实施混沌搜索, 直至满足迭代收敛条件为止。CPSO算法能提高种群的多样性和粒子搜索的遍历性, 从而有效提高了PSO算法的收敛速度和精度。两个工程约束优化实例的求解结果表明,该算法的优化结果最好, 收敛速度也比较快-Based on engineering design optimization problems, and put forward based on chaotic particle swarm optimization algorithm of engineering problem solving methods. CPSO algorithm by using chaos search The global ergodicity, stochastic characteristics and regularity, and lead particles in the global scope search, and overcome the traditional particle swarm algorithm premature convergence faults. In this algorithm, the population fitness variance as the particle swarm optimization algorithm of the criterion of premature convergence, the penalty function method and deal with illegal constraint particles, when basic particle swarm to calculate Law in early maturity, random selection of particle swarm of these particles implementation chaotic search, until the convergence conditions meet so far. CPSO algorithm can improve the population Sample sex and particles of searching ergodicity, thus effectively improved PSO algorithm convergence speed and accuracy. Two engineering constraint optim
Date : 2025-12-26 Size : 728kb User : 吴胜亮
[AI-NN-PR] pso DL : 0: 粒子群算法及其优化算法，已经运行过。测试函数在fitness.m中添加-pso and so on
Date : 2025-12-26 Size : 17kb User : 火柴
[AI-NN-PR] Multi-Agent-Particle-Swarm-Algorithm DL : 0: 结合多智能体的学习、协调策略及粒子群算法，提出了一种基于多智能体粒子群优化的配电网络重构方法。该方法采用粒子群算法的拓扑结构来构建多智能体的体系结构，在多智能体系统中，每一个粒子作为一个智能体，通过与邻域的智能体竞争、合作。能够更快、更精确地收敛到全局最优解。粒子的更新规则减少了算法不可行解的产生，提高了算法效率。实验结果表明，该方法具有很高的搜索效率和寻优性能。-Combining the study of multi-agent technology，coordinating strategies with P$O，a Multi-Agent Particle Swarm Optimization(MA-PSO)algorithm is presented to handle distribution network reconfiguration problem．It applies Von Neuman architecture of Particle Swarm Optimization algorithm to the composition of multi-agent system．An agent in MA-PSO represents a particle to PSO and a candidate solution to the optimization problem．In order to decrease fitness value quickly，agents compete and cooper-ate with their agent of neighboring area．Making use of these agent—agent interactions，MA—PSO realizes the purpose of minimizing the value of objective function．The rules of particle renovating reduce unfeasible solution in the process of particle renovating，which raises the algorithm efficiency satty．The experiment results indicate the prominent efficiency and significant global optima searching performance of MS—PSO．
Date : 2025-12-26 Size : 503kb User : yirufang
[AI-NN-PR] Demo-(1) DL : 0: pso中的rosenbrock适应度函数-pso in the rosenbrock of the fitness function
Date : 2025-12-26 Size : 50kb User : 黄轩
[AI-NN-PR] PSO-BP DL : 1: PSO算法从随机解出发，通过迭代寻找最优解，通过适应度来评价解的品质，粒子群优化Bp网络源程序，仅供参考-PSO algorithm from random solutions to find the optimal solution by iteration, the fitness evaluation solution quality, particle swarm optimization Bp network source, for reference only
Date : 2025-12-26 Size : 760kb User : 曹亚军
[AI-NN-PR] Dissertation-For-PSO DL : 0: 一篇关于粒子群算法的毕业论文，文中对算法进行了详细分析，并在Matlab环境下，对算法不同的适应度进行了仿真和分析。-A thesis on particle swarm optimization, the text of the algorithm are analyzed in detail in the Matlab environment, simulation and analysis algorithms fitness.
Date : 2025-12-26 Size : 830kb User : ocean
[AI-NN-PR] APSO DL : 1: 这是引入了自适应权重特征的粒子群优化算法，其中的通过粒子在整个群中的适应值顺序进行惯性权重的计算，提高了标准粒子群的性能，对于初学者具有很大的帮助-This is the introduction of adaptive weights characteristic particle swarm optimization algorithm, which through the particle in the whole group of fitness order inertia weight is calculated to improve the performance of the standard PSO, great help for beginners
Date : 2025-12-26 Size : 4kb User : Arogon
[AI-NN-PR] fitness DL : 0: 在基本PSO算法的基础上，采用单纯体法进行初始化，并引入变异因子，同时对基本PSO算法的公式和参数进行修正。-On the basis of basic PSO algorithm, using a simple method to initialize the body, and the introduction of variability factor, while the basic PSO algorithm to correct formulas and parameters.
Date : 2025-12-26 Size : 2kb User : zhangxiaoqing
[AI-NN-PR] fit-pso DL : 0: 带fitness的粒子群算法，希望为研究pso的人们提供一个功能较为完备、简单易学的标准版本，-PSO algorithm with fitness is provided people who want to study PSO a more complete, easy standard version,
Date : 2025-12-26 Size : 1kb User : liwenquan_168
[AI-NN-PR] pso DL : 0: MATLAB标准粒子群算法（pso）例子，求fitness中的函数最小。-MATLAB particle swarm example, seeking the fitness function is minimized.
Date : 2025-12-26 Size : 3kb User : 李永胜
[AI-NN-PR] PSO toolbox DL : 0: 粒子群算法工具箱以及适应度函数实例，实测有效(Particle swarm algorithm toolbox, as well as fitness function example, effective measurement)
Date : 2025-12-26 Size : 745kb User : 飞哥哥
[AI-NN-PR] 模式识别与智能计算-matlab技术实现 DL : 0: 简单的PSO算法代码，但是需要添加fitness函数。(Simple PSO algorithm code, but need to add fitness function.)
Date : 2025-12-26 Size : 25.21mb User : 王大仙儿
[AI-NN-PR] PSO-Python DL : 0: 粒子群算法，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 particle swarm optimization (PSO) algorithm, which is one of the evolutionary algorithms, is similar to the simulated annealing algorithm. It also starts from the random solution to find the optimal solution by iteration. It also evaluates the quality of the solution by the fitness, but it is more simple than the genetic algorithm rule, and it has no genetic algorithm "Crossover" and "variation". "(Mutation) operation, it seeks the global optimum by following the best value that is currently searched. This algorithm has attracted the attention of the academic community for its advantages of easy realization, high accuracy and fast convergence, and has shown its superiority in solving practical problems. Particle swarm optimization (PSO) is a parallel algorithm.)
Date : 2025-12-26 Size : 4kb User : 绝情逆空

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