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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Author:张正 |
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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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Author: |
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Description: pso粒子群优化算法程序 加了实现模糊功能的新算法。-PSO PSO algorithm processes the realization of the new and fuzzy algorithm. Platform: |
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Author:jun |
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Description: 多目标粒子群的matlab程序，文中设置了两个目标，f1和f2，采用加权求解的方式-more goals in Matlab PSO procedures, the text set up two goals, f1 and f2. using the weighted solution! Platform: |
Size: 2048 |
Author:张波 |
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Description: 该算法为基于sugeno的倒立摆模糊控制
用MATlab开发，能够管直接运行-The algorithm for the Sugeno-based fuzzy control of inverted pendulum using Matlab development, be able to pipe directly to run Platform: |
Size: 2048 |
Author:wujianzhang |
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Description: 用隶属函数型神经网与模糊控制融合的解耦程序-Membership functions with neural networks and fuzzy control integration of the decoupling procedure Platform: |
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Author:娟娟 |
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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: This M-file is about using Particle Swarm Algorithm (PSO) to train a Fuzzy Neural Network. Platform: |
Size: 1024 |
Author:Mehran Ahmadlou |
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Description: 模糊粒子群的MATLAB实现，我们知到粒子群是一种智能方法-MATLAB fuzzy particle swarm to achieve, we know that PSO is an intelligent way Platform: |
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Author:王科 |
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Description: 基于模糊规则的pso算法，用MATLAB编写的,绝对可用-Pso algorithm based on fuzzy rules, written using MATLAB, absolutely free Platform: |
Size: 2048 |
Author:gsy |
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Description: 本书共有30个MATLAB神经网络的案例,包括BP、RBF、SVM、SOM、Hopfield、LVQ、Elman、小波等神经网络,还包含PSO(粒子群)、灰色神经网络、模糊网络、概率神经网络、遗传算法优化等内容。-The book consists of 30 MATLAB neural network case (including program can be run), including BP, RBF, SVM, SOM, Hopfield, LVQ, Elman, wavelet neural networks, etc. also contains the PSO (PSO), gray neural networks, fuzzy networks, probabilistic neural networks, genetic algorithm optimization and so on. Platform: |
Size: 28765184 |
Author:万二 |
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Description:
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ypea121-mopso
Multi-Objective PSO in MATLAB
in Multiobjective Optimization 8 Comments 2,599 Views
Multi-Objective Particle Swarm Optimization (MOPSO) is proposed by Coello Coello et al., in 2004. It is a multi-objective version of PSO which incorporates the Pareto Envelope and grid making technique.-
Home
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Home \ Multiobjective Optimization \ Multi-Objective PSO in MATLAB
ypea121-mopso
Multi-Objective PSO in MATLAB
in Multiobjective Optimization 8 Comments 2,599 Views
Multi-Objective Particle Swarm Optimization (MOPSO) is proposed by Coello Coello et al., in 2004. It is a multi-objective version of PSO which incorporates the Pareto Envelope and grid making technique. Platform: |
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Author:ankita |
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