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: |
Size: 16633 |
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: 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: 粒子群程序,是一种有效的优化算法,用于控制-Particle swarm procedure is an effective optimization algorithm is used to control Platform: |
Size: 2048 |
Author:Liang |
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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: 使用基本粒子群算法整定的PID控制，供学习者参考。-The use of elementary particle swarm optimization algorithm-tuning PID control for the learner information. Platform: |
Size: 21504 |
Author:zangtianlei |
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Description: 基于粒子群算法的高速公路速度可变控制。可以用来仿真-Based on particle swarm optimization variable speed control of the highway. Simulation can be used to Platform: |
Size: 2048 |
Author:罗权 |
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Description: 该文件为粒子群算法优化支持向量机模型参数的matlab代码
支持向量机模型为专门用于处理不平衡数据的成本控制型支持向量机模型
用粒子群算法优化模型中的三个主要参数：C1、C2、sigma-The file is in particle swarm optimization parameters of support vector machine model matlab code for support vector machine model designed for use with unbalanced data, cost control, support vector machine model using particle swarm optimization model of the three main parameters: C1, C2, sigma Platform: |
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Author:yudt002 |
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Description: 基于改进粒子群算法的中药提取过程PID优化控制Based on improved particle swarm optimization of PID control of the extraction process of Chinese medicine-Based on improved particle swarm optimization of PID control of the extraction process of Chinese medicine Platform: |
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Author: |
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Description: 研究基于粒子群算法控制系统PID参数优化设计方法以及对PID控制的改进。- study the optimal design of PID parameter of the control system based on Particle Swarm Optimization and find a way to improve the PID control. Platform: |
Size: 267264 |
Author:durongmao |
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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。
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 computing (evolutionary computation), there is invented by Dr. Eberhart and Dr. kennedy. From the behavior of birds of prey. PSO with genetic algorithm is similar to an iteration-based optimization tool. System is initialized to a group of random solutions, the optimal value by iterative search. But there is no genetic algorithm with the cross (crossover) and mutation (mutation). But the particles in the solution space to follow the optimal particle search. Comparison with genetic algorithms, PSO has the advantage of simple and easy to implement and there is no need to adjust many parameters. Has been widely used in function optimization, neural network training, fuzzy system control, and other genetic algorithm applications. Platform: |
Size: 10240 |
Author:天涯 |
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Description: Routing and Load balancing in MANET using Particle Swarm Optimization
Abstract
Mobile Ad Hoc Networks (MANET) is a collection of wireless mobile nodes, which dynamically form a temporary network, without using any existing network infrastructure or centralized administration. These are often called infrastructure-less networking since the mobile nodes in the network dynamically establish routing paths between themselves. Routing which is responsible for directing data packets from a source node to a given destination node is one of the hard tasks in MANET, this is due to the mobility of the network elements and the lack of central control. Although Platform: |
Size: 7168 |
Author:Riham |
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Description: The performance of fuzzy logic (FLC)control optimized by particle swarm optimization (PSO) for semi-active suspension system using magneto-rheological (MR) damper . MR damper is an intelligent damper filled with particle magnetic polarizable and suspended into a liquid form. The Bouc-Wen model of MR damper is used to determine the required damping force based on force-displacement and force-velocity characteristics. Platform: |
Size: 281600 |
Author:mido |
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Description: Improved Particle Swarm Optimization Based
Load Frequency Control In
A Single Area Power System Platform: |
Size: 305152 |
Author:hassan |
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Description: 小型四旋翼的智能控制。使用基于粒子群的PID控制、基于遗传算法的PID控制，以及BP神经网络控制-小型四旋翼的智能控制。使用基于粒子群的PID控制、基于遗传算法的PID控制，以及BP神经网络控制。Simulation of Intelligent Control for Quadrotor， which based on particle swarm optimization PID control, genetic algorithhm PID control and BP neural network PID control. Platform: |
Size: 11653120 |
Author:CMC |
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Description: 针对直流电网中的最优潮流问题，提出了一种基于模糊控制理论的自适应粒子群算法，以实现电网兼顾有功网损和电压质量的优化运行。(To solve optimal power flow problem in DC grid, an adaptive particle swarm optimization (PSO) algorithm based on fuzzy control theory is proposed in this paper, and optimal operation considering both power loss and voltage quality is realized.) Platform: |
Size: 302080 |
Author:阿飞之父 |
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Search - control particle swarm optimization