Description: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation).源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary technology (evolutionary computation). Predatory birds originated from the research PSO with similar genetic algorithm is based on iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values. However, there is no genetic algorithm with the cross- (crossover) and the variation (mutation). But particles in the solution space following the optimal particle search. The steps detailed chapter on the future of genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and other genetic algorithm applications Platform: |
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Description: 粒子群优化算法（PSO）是一种进化计算技术（evolutionary computation）,由Eberhart博士和kennedy博士于1995年提出 (Kennedy J，Eberhart R．
Particle swarm optimization．Proceedings of the IEEE International Conference on Neural Networks．1995．1942~1948.)。源于对鸟群捕食的行为研究。粒子群优化算法的基本思想是通过群体中个体之间的协作和信息共享来寻找最优解．
-Particle Swarm Optimization (PSO) is an evolutionary computation techniques (evolutionary co mputation) by Dr. Eberhart and kennedy Dr. raised in 1995 (Kennedy, J., Eberhart R. Particle swarm optimization.Proc eedings of the IEEE International Conference o n Neural Networks.1995.1942 ~ 1948.) . From the flock of the predatory behavior. PSO algorithm is the basic idea of individual groups through the sharing of information and collaboration to find the optimal solution. Platform: |
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Author:周荷 |
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Description: 这是一个pso程序源代码，pso源于对鸟群捕食行为的研究而发明的进化计算技术，属于进化算法的一种。
优点：收敛速度快，具有全局寻优能力，而且编程简单，易于推广使用。 -This is a pso source code, pso out of the flock of predatory behavior and evolutionary computation invention of the technology is an evolutionary algorithm. Advantages : fast convergence with global optimization capability and programming simple and easy to use. Platform: |
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Author:张清 |
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Description: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)，有Eberhar博士和kennedy博士发明。源于对鸟群捕食的行为研究 ，PSO同遗传算法类似，是一种基于叠代的优化工具。
-Particle Swarm Optimization (PSO) is an evolutionary computation technique (evolutionary computation), and has Eberhar Dr. Dr. kennedy invention. Stems from the behavior of predatory birds, PSO with genetic algorithm is similar to an iterative optimization-based tools. Platform: |
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Author:叶开 |
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Description: 这是解决另外问题的PSO进化算法源程序,里面有注释,易于学习.我正在写硕士论文,写好后,会把我的成果共享,请把我加为VIP会员,谢谢.-This is the solution to another problem source PSO evolutionary algorithm, which has notes, easy to learn. I was writing a master Platform: |
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Author:强 |
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Description: 此压缩文件中包含了两个读取bmp文件分别用java和c写了,另三个是用matlab实现的演化算法,很有作用的,每个文件里都有详细说明-This compressed file contains two read bmp file with java and c, respectively, wrote the other three is the realization of the evolutionary algorithm matlab, it is the role of each document has a detailed description Platform: |
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Author:Joney |
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Description: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation)，有Eberhart博士和kennedy博士发明。源于对鸟群捕食的行为研究
PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍
同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary computation technique (evolutionary computation), has Dr. Eberhart and Dr. kennedy invention. Deriving from the behavior of birds of prey PSO with genetic algorithm is similar to an iterative optimization-based tools. System initialization for a group of random solutions, through the iterative search for optimal values. But there is no cross-genetic algorithm used (crossover) and mutation (mutation). But the particles in the solution space of the particles to follow the optimal search. In detail the steps after the introduction sections compared with the genetic algorithm, PSO has the advantage of being simple and easy and did not realize many of the parameters need to be adjusted. Has been widely applied to function optimization, neural network training, fuzzy system control, as well as other genetic algorithm applications Platform: |
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Author:zzh |
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Description: 微粒群算法[PSO ] 是由Kennedy 和Eberhart等于1995 年开发的一种演化计算技术, 来源于对鸟群捕食过程的模拟。PSO同遗传算法类似，是一种基于叠代的优化工具，但与遗传算法使用遗传操作子进行优化不同，利用群体中各个体之间的“协作”与“竞争”关系，根据自身及其竞争者的飞行经验，调整自己的行为。同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域。-Particle Swarm Optimization [PSO] are equal by Kennedy and Eberhart in 1995 developed an evolutionary computing technology, from preying on the birds of the simulation process. PSO with genetic algorithm is similar to an iterative optimization-based tool, but the use of genetic algorithms and genetic manipulation of different sub-optimize the use of groups between the various entities within the " collaboration" and " competitive" relationship, according to themselves and their competition the flying experience, adjust their behavior. Comparison with genetic algorithms, PSO has the advantage of being simple and easy and did not realize the need to adjust the parameters much. Has been widely applied to function optimization, neural network training, fuzzy system control, as well as other genetic algorithm applications. Platform: |
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Author:wzy |
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Description: Java平台的启发式优化算法，包含了多目标进化算法（SPEA2和NSGA2），多目标差异进化，PSO和单目标模拟退火算法。并且包含了ZDT,DTLZ和WFG等测试函数-Opt4J is a framework for applying meta-heuristic optimization algorithms to arbitrary optimization problems.
The Opt4J framework currently includes a multi-objective Evolutionary Algorithm (including SPEA2 and NSGA2), a multi-objective Differential Evolution, a multi-objective Particle Swarm Optimizer (PSO), and a single-objective Simulated Annealing with some predefined cooling schedules. The Opt4J framework also contains several benchmarks like ZDT, DTLZ, or WFG. Platform: |
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Author:stuart |
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Description: 微粒群优化算法 （PSO） 是一种进化计算技术 , 由Eberhart博士和kennedy博士于1995年提出。微粒群优化算法的基本思想是通过群体中个体之间的协作和信息共享来寻找最优解。
-Particle Swarm Optimization (PSO) is an evolutionary computation technique, by Dr. Eberhart and Dr. kennedy made in 1995. Particle Swarm Optimization Algorithm The basic idea of the individual through group collaboration and information sharing between to find the optimal solution. Platform: |
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Author:Kevin |
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Description: 粒子群优化算法是一种进化优化技术，源于对鸟群扑食的行为，是一种基于迭代的优化工具。此文件提供了基本粒子群算法、带压缩因子的粒子群算法、二阶粒子群算法、二阶振荡粒子群算法、权重改进的粒子群算法、混沌粒子群算法、基于杂交的粒子群算法、基于模拟退火的粒子群算法的MATLAB源代码。-PSO is an evolutionary optimization technique, derived from the behavior of the birds of prey, is based on iterative optimization tools. This document provides basic particle swarm algorithm, with a compression factor of the particle swarm algorithm, particle swarm optimization order, second order oscillating particle swarm algorithm, the weight particle swarm algorithm, chaotic particle swarm algorithm, based on hybrid particle swarm algorithm, based on Simulated annealing particle swarm optimization MATLAB source code. Platform: |
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Author:熊杰 |
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Description: The economic load dispatch plays an important role in the operation of power system,
and several models by using different techniques have been used to solve these problems.
Several traditional approaches, like lambda-iteration and gradient method are utilized to find out
the optimal solution of non-linear problem. More recently, the soft computing techniques have
received more attention and were used in a number of successful and practical applications. The
purpose of this work is to find out the advantages of application of the evolutionary computing
technique and Particle Swarm Optimization (PSO) in particular to the economic load dispatch
problem. Here, an attempt has been made to find out the minimum cost by using PSO using the
data of three and six generating units Platform: |
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Author:amijeet |
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Description: 粒子群优化算法是一种基于群体智能的演化计算技术。与遗传算法相比，PSO没有遗传算法中的选择(Selection)、交叉(Crossover)、变异(Mutation)等操作，而是通过粒子在解空间追随最优的粒子进行搜索。(Particle Swarm Optimization (PSO) is an evolutionary computing technique based on group intelligence. Compared with the genetic algorithm, PSO has no selection, selection (crossover), mutation (Mutation) and other operations in the genetic algorithm, but through the particles in the solution space to follow the optimal particle search.) Platform: |
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Author:lazyxiaoming
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Description: 粒子群优化算法(PSO：Particle swarm optimization) 是一种进化计算技术（evolutionary computation）。
源于对鸟群捕食的行为研究。粒子群优化算法的基本思想：是通过群体中个体之间的协作和信息共享来寻找最优解．
PSO的优势：在于简单容易实现并且没有许多参数的调节。目前已被广泛应用于函数优化、神经网络训练、模糊系统控制以及其他遗传算法的应用领域。(The particle swarm optimization (PSO:Particle swarm optimization) is an evolutionary computing technology (Evolutionary Computation).
The study of the behavior of bird predator. The basic idea of particle swarm optimization (PSO) is to find the optimal solution through the collaboration and information sharing among the individuals in the group.
The advantage of PSO is that it is simple and easy to implement without many parameters. At present, it has been widely used in function optimization, neural network training, fuzzy system control and other genetic algorithms.) Platform: |
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Author:安联的大球童 |
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Description: 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.) Platform: |
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Author:cinderella345 |
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Description: 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.) Platform: |
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Author:绝情逆空 |
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