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给出了经典的粒子群优化算法的matlab实现方法，并结合测试函数，显示算法的寻优能力-Gives a classical particle swarm optimization algorithm matlab implementation, combined with the test function, the ability to display optimization algorithm
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经典粒子群算法的matlab实现。用多维函数进行测试。并给出算法寻优迭代的效果图-Classical PSO algorithm matlab. Tested with multi-dimensional functions. And gives an iterative optimization algorithm renderings
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经典粒子群算法的matlab实现。用函数进行测试实验，并给出算法寻优迭代的效果图-Classical PSO algorithm matlab. Experiments with test functions, and gives an iterative optimization algorithm renderings
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经典粒子群算法的matlab实现代码。用函数进行测试实验，并给出算法寻优迭代的效果图-Classical PSO algorithm matlab. Experiments with test functions, and gives an iterative optimization algorithm renderings
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This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are
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This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are
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This work investigates the practical application of
support vector machine (SVM) to power transformer condition
assessment. Partiuclarly, this paper proposes to integrate the
SVM algorithm with two heuristic optimization algorithms which
are
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Matlab PSO
In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having
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This document introduces the Particle Swarm Optimization (PSO) in Scilab.
The PSO method, published by Kennedy and Eberhart in 1995,
is based on a population of points at first stochastically
deployed on a search field.
Each member
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用PSO算法求解多目标优化问题，每一行都有详细注释，可直接运行。-Solving multi-objective optimization problem with PSO algorithm, each line has detailed notes, can be directly run.
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这个程序就是最基本的粒子群优化算法程序，用Matlab实现。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。-This program is the most basic particle swarm optimization procedures, using Matlab to achieve. Optimizing the function with the form of m documents on fitness.m
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利用粒子群算法求解全局最优值，并附有图形-Using particle swarm optimization (pso) algorithm solving the global optimal value, and with the graphics
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Using Matlabe wrote PSO optimization algorithm with swarm_data.
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optimization with iteration pso
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粒子群算法的Matlab程序实现。不仅提供了源程序，还附带有详细的例子。对于初学者有极大的帮助。-PSO algorithm Matlab programming. Not only provides a source, also comes with detailed examples. There are a great help for beginners.
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In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.
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pso 粒子群优化算法 以简单的函数为例，展示基本算法-PSO particle swarm optimization algorithm with simple function as an example, show the basic algorithm
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In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population
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将SVM与粒子群算法(PSO)相结合,充分利用SVM在处理小样本回归问题上具有的独特优越性及PSO全局搜索优化等特点-SVM and particle swarm optimization algorithm (PSO) combined with SVM, makes full use of the unique superiority and the PSO global search optimization features in small sample regression prob
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各种粒子群或改进型粒子群算法
1）粒子群优化算法(求解无约束优化问题)
1>PSO(基本粒子群算法)
2>YSPSO(待压缩因子的粒子群算法)
3>LinWPSO(线性递减权重粒子群优化算法)
4>SAPSO(自适应权重粒子群优化算法)
5>RandWSPO(随机权重粒子群优化算法)
6>LnCPSO(同步变化的学习因子)
7>AsyLnCPSO(异步变化的学习因子)(算法还有bug)
8>SecPSO(用二阶粒
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