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Particle swarm optimization (PSO) is a population based stochastic optimization technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling. Each particle keeps track of its coordinates
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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 iter
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应用共轭梯度法综合优化交叉耦合滤波器。参考文献<Synthesis of Cross-coupled’Resonator Filters Using an Analytical Gradient-Based Optimization Technique >Smain Amari-Synthesis of Cross-coupled’Resonator Filters Using an Analytical Gradient-Based Optimization Technique _
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The Nelder–Mead method or downhill simplex method or amoeba method is a commonly used nonlinear optimization technique, which is a well-defined numerical method for twice differentiable and unimodal problems. However, the Nelder–Mead technique is onl
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Locally-Linear Embedding (LLE)[9] was presented at approximately the same time as Isomap. It has several advantages over Isomap, including faster optimization when implemented to take advantage of sparse matrix algorithms, and better results with man
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matlab最优化20个实例，看了就知道物有所值了，对于学习优化的朋友很有用。-20 instances of matlab optimization, read to know that value for money, and friends for useful learning optimization.
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微粒群优化算法（PSO）是一种基于种群的随机优化技术，由Eberhart和Kennedy于1995年提出。微粒群算法模仿昆虫、兽群、鸟群和鱼群等的群集行为，这些群体按照一种合作的方式寻找食物，群体中的每个成员通过学习它自身的经验和其他成员的经验来不断改变其搜索模式。-Particle Swarm Optimization (PSO) is a population based stochastic optimization technique by Eberhart and Kennedy ma
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cuckoo search an evolutionary algorithm in optimization technique
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mamdani based optimization technique
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Using ITSE as objective function tuning of PI controller using Particle Swarm Optimization technique
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这是关于粒子群算法的一篇综述论文，说明了PSO算法的原理，及其算法流程！-PSO is a population-based stochastic optimization technique inspired by social behavior of bird flocking or fish schooling. All of particles have fitness values which are evaluated by the fitness function to be op
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Ant colony optimization technique
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ant colony optimization technique for JSSP
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同时考虑了应用的实时性和网络的能源有效性，提出了一种基于GA的嵌套优化技术，并在多跳聚簇网络中进行能源高效的任务分配-Taking into account the energy efficiency of real-time application and network optimization technique based on GA nested, and energy efficient task allocation in multi-hop clustered network
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Genetic algorithms (GA) is an optimization technique for
searching very large spaces that models the role of the genetic material in
living organisms. A small population of individual exemplars can e ectively
search a large space because they c
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PSO was originally introduced as an optimization technique for continuous space. in order to
extend the application to discrete spaces, Kennedy and Eberhart [43] proposed a discrete binary
version of PSO where a particle moves in a state space re
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方案适用于典型的TSP问题的蚁群优化技术。
是改进版,效果比较好！对想研究蚁群聚类算法并要写出好文章的朋友，很有用！This program applies the typical ant colony optimization technique on TSP problem. -This program applies the typical ant colony optimization technique on TSP problem.
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Powell s Optimization technique used for image processing.
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PID tuning by using Gravitational Search Algorithm (GSA). GSA is new algorithm which is believed can produce a better result compare to other optimization technique
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粒子群算法（PSO）是一种基于群体的随机优化技术。与其它基于群体的进化算法相比，它们均初始化为一组随机解，通过迭代搜寻最优解。不同的是：进化计算遵循适者生存原则，而PSO模拟社会。将每个可能产生的解表述为群中的一个微粒，每个微粒都具有自己的位置向量和速度向量，以及一个由目标函数决定的适应度。所有微粒在搜索空间中以一定速度飞行，通过追随当前搜索到的最优值来寻找全局最优值。 -Particle swarm optimization (PSO) is a kind of stochastic opti
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