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Description: 粒子群优化算法!!!
系统地介绍了粒子群优化算法,归纳了其发展过程中的各种改进如惯性权重!收敛因子!跟踪并
优化动态目标等模型\"阐述了算法在目标函数优化!神经网络训练!模糊控制系统等基本领域的应用并
给出其在工程领域的应用进展,最后,对粒子群优化算法的研究和应用进行了总结和展望,指出其在计算
机辅助工艺规划领域的应用前景\"-PSO algorithm! ! ! A systematic introduction to PSO algorithm, summed up its development process such as the improvement of inertia weight! Convergence factor! track and dynamic optimization model objectives, "explained the algorithm optimization objective function! Neural Network Training! Fuzzy Control System basic areas of application and gives the project from its the application domain, finally, the PSO algorithm research and application of the summary and outlook. pointed out in the field of computer-aided process planning applications prospects "
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Author: 八云 |
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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
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Description: 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-comparison with the 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
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Size: 16384 |
Author: wxd |
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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.
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Size: 2048 |
Author: jun |
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Description: 粒子群优化算法!!!
系统地介绍了粒子群优化算法,归纳了其发展过程中的各种改进如惯性权重!收敛因子!跟踪并
优化动态目标等模型"阐述了算法在目标函数优化!神经网络训练!模糊控制系统等基本领域的应用并
给出其在工程领域的应用进展,最后,对粒子群优化算法的研究和应用进行了总结和展望,指出其在计算
机辅助工艺规划领域的应用前景"-PSO algorithm! ! ! A systematic introduction to PSO algorithm, summed up its development process such as the improvement of inertia weight! Convergence factor! track and dynamic optimization model objectives, "explained the algorithm optimization objective function! Neural Network Training! Fuzzy Control System basic areas of application and gives the project from its the application domain, finally, the PSO algorithm research and application of the summary and outlook. pointed out in the field of computer-aided process planning applications prospects "
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Size: 53248 |
Author: 八云 |
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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
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Size: 22528 |
Author: zzh |
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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
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Size: 2048 |
Author: wujianzhang |
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Description: This M-file is about using Particle Swarm Algorithm (PSO) to train a Fuzzy Neural Network.
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Size: 1024 |
Author: Mehran Ahmadlou |
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Description: basic pso code combined with fuzzy
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Size: 5120 |
Author: Vijay |
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Description: pso with Fuzzy document
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Size: 25600 |
Author: Vijay |
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Description: Fuzzy PSO算法仿真源代码,实现模糊蚁群优化算法的仿真。-Fuzzy PSO algorithm
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Author: sukuifeng |
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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
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Size: 2048 |
Author: gsy |
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Description: 2008 Exploiting User Logsin CBI Rusing fuzzy PSO
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Size: 128000 |
Author: fathemeh |
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Description: 基于模糊Havrda_Charv_t熵与混沌PSO算法的红外人体图像分割-Entropy and chaos based on fuzzy Havrda_Charv_t PSO algorithm image segmentation of infrared body
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Size: 662528 |
Author: zixi2000 |
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Description: 详细给定了模糊PSO模型算法,可以用于matlab工具箱-PSO Fuzzy Modeler for MATLAB
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Size: 204800 |
Author: cathy |
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Description: PSO算法简单、易实现且参数较少,现已被应用于函数优化、神经网络训练、模糊系统控制以及其它遗传算法的应用领域-PSO algorithm is simple, easy to implement and less parameters, have been applied to function optimization, neural network training, fuzzy system control and other applications of genetic algorithms
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Size: 216064 |
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Description: another papers on the fuzzy logic for pso, this papers provides excellent discussions on the algorithms, you must have a copy of this one
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Size: 6801408 |
Author: seven string |
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Description: 2017 Fuzzy-PSO controller design for maximum power point tracking in photovoltaic system
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Size: 917504 |
Author: hieuhuech1
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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.)
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Size: 5120 |
Author: 安联的大球童 |
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Description: matlab code for tsp using pso
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Size: 400384 |
Author: usgaa |
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