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[
matlab
]
PSO-evolutionarycomputation
DL : 0
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
Date
: 2026-01-18
Size
: 22kb
User
:
zzh
[
matlab
]
pso
DL : 1
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 iterative optimization tools. This document provides basic particle swarm algorithm, with a compression factor of the particle swarm algorithm, particle swarm optimization order, second order oscillating particle swarm algorithm, the weight particle swarm algorithm, chaotic particle swarm algorithm, based on hybrid particle swarm algorithm, based on Simulated annealing particle swarm optimization MATLAB source code.
Date
: 2026-01-18
Size
: 16kb
User
:
熊杰
[
matlab
]
pso
DL : 0
The economic load dispatch plays an important role in the operation of power system, and several models by using different techniques have been used to solve these problems. Several traditional approaches, like lambda-iteration and gradient method are utilized to find out the optimal solution of non-linear problem. More recently, the soft computing techniques have received more attention and were used in a number of successful and practical applications. The purpose of this work is to find out the advantages of application of the evolutionary computing technique and Particle Swarm Optimization (PSO) in particular to the economic load dispatch problem. Here, an attempt has been made to find out the minimum cost by using PSO using the data of three and six generating units
Date
: 2026-01-18
Size
: 530kb
User
:
amijeet
[
matlab
]
pso
DL : 0
粒子群算法,也称粒子群优化算法(Particle Swarm Optimization),缩写为 PSO, 是近年来发展起来的一种新的进化算法((Evolu2tionary Algorithm - EA)。PSO 算法属于进化算法的一种,和遗传算法相似,它也是从随机解出发,通过迭代寻找最优解,它也是通过适应度来评价解的品质,但它比遗传算法规则更为简单,它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作,它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视,并且在解决实际问题中展示了其优越性。-Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years ((Evolu2tionary Algorithm- EA) .PSO algorithm is an evolutionary algorithm, and similar genetic algorithm, it is also starting random solutions, through iterative search for the optimal solution, which is also uated by the quality of the fitness solution, but it is much simpler than genetic algorithms rule, it does not have the genetic algorithm cross (Crossover) and variant (Mutation) operation, which by following the current search to find the optimal value to the global optimum. the algorithm for its easy implementation, high accuracy, and fast convergence advantages attracted academic attention, and in solving practical problems demonstrated its superiority.
Date
: 2026-01-18
Size
: 7kb
User
:
了了
[
matlab
]
PSO
DL : 0
粒子群算法,也称粒子群优化算法(Particle Swarm Optimization),缩写为 PSO, 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种,和模拟退火算法相似,它也是从随机解出发,通过迭代寻找最优解,它也是通过适应度来评价解的品质,但它比遗传算法规则更为简单,它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作,它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视,并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。-Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm.
Date
: 2026-01-18
Size
: 2kb
User
:
艾岳巍
[
matlab
]
pso-bp
DL : 0
粒子群算法,也称粒子群优化算法(Particle Swarm Optimization),缩写为 PSO, 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种,和模拟退火算法相似,它也是从随机解出发,通过迭代寻找最优解,它也是通过适应度来评价解的品质,但它比遗传算法规则更为简单,它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作,它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视,并且在解决实际问题中展示了其优越性。粒子群算法是一种并行算法。 BP(Back Propagation)神经网络是1986年由Rumelhart和McCelland为首的科学家小组提出,是一种按误差逆传播算法训练的多层前馈网络,是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系,而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法,通过反向传播来不断调整网络的权值和阈值,使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层(input)、隐层(hidden layer)和输出层(output layer)。-Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm. BP (Back Propagation) neural network is a 1986 team of scientists headed by Rumelhart and McC
Date
: 2026-01-18
Size
: 2kb
User
:
艾岳巍
[
matlab
]
Code-FLC-ANFIS-GA-PSO
DL : 0
We describe in this paper a new hybrid approach for mathematical function optimization combining Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) using Fuzzy Logic for parameter adaptation and integrate the results. The new evolutionary method combines the advantages of the fuzzy logic to give us an improved FPSO+FGA hybrid method. Fuzzy Logic is used to combine the results of the PSO and GA in the best way possible.
Date
: 2026-01-18
Size
: 184kb
User
:
hari
[
matlab
]
liziqun
DL : 0
粒子群寻优算法,pso,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。-Particle swarm optimization algorithm, pso, PSO is an evolutionary optimization technology, birds originated the prey' s behavior is based on an iterative optimization tools.
Date
: 2026-01-18
Size
: 2kb
User
:
筱玉
[
matlab
]
Evolutionary-ANFIS-Training
DL : 2
用MATLAB实现自适应神经模糊推理系统(ANFIS)结构训练。代码中,首先创建一个初始原ANFIS结构,然后采用遗传算法(GA)、粒子群优化(PSO)来训练ANFIS。此进化训练算法可用于解决非线性回归函数逼近问题。-Implementation of adaptive neural fuzzy inference system (ANFIS) based on MATLAB. Code, the first to create an initial original ANFIS structure, and then using the genetic algorithm (GA), particle swarm optimization (PSO) to train ANFIS. This evolutionary training algorithm can be used to solve the nonlinear regression function approximation problem.
Date
: 2026-01-18
Size
: 21kb
User
:
张贝
[
matlab
]
MOPSO
DL : 0
MOPSO matlab code- (Multi-Objective Particle Swarm Optimization algorithm) - An evolutionary multi-objective optimization algorithm
Date
: 2026-01-18
Size
: 10kb
User
:
Ehsan
[
matlab
]
PSO算法程序
DL : 0
粒子群优化算法是一种基于群体智能的演化计算技术。与遗传算法相比,PSO没有遗传算法中的选择(Selection)、交叉(Crossover)、变异(Mutation)等操作,而是通过粒子在解空间追随最优的粒子进行搜索。(Particle Swarm Optimization (PSO) is an evolutionary computing technique based on group intelligence. Compared with the genetic algorithm, PSO has no selection, selection (crossover), mutation (Mutation) and other operations in the genetic algorithm, but through the particles in the solution space to follow the optimal particle search.)
Date
: 2026-01-18
Size
: 10kb
User
:
lazyxiaoming
[
matlab
]
IEEE 30 bus system data
DL : 0
IEEE 30 BUS SYSTEM Comparisons between stochastic and deterministic Unit Commitment solutions are provided. The generation of Unit Commitment solution is guaranteed by DEEPSO, which is a hybrid DE-EA-PSO algorithm, where DE stands for Differential Evolution, EA for Evolutionary Algorithms and PSO for Particle Swarm Optimization. For the calculation of the optimal economic dispatch an algorithm based on the Benders Decomposition, combining the Dual Dynamic Programming, was developed. Results show that the stochastic approach leads to more ro
Date
: 2026-01-18
Size
: 130kb
User
:
therealneel7
[
matlab
]
Current methods and advances in forecasting
DL : 0
Comparisons between stochastic and deterministic Unit Commitment solutions are provided. The generation of Unit Commitment solution is guaranteed by DEEPSO, which is a hybrid DE-EA-PSO algorithm, where DE stands for Differential Evolution, EA for Evolutionary Algorithms and PSO for Particle Swarm Optimization. For the calculation of the optimal economic dispatch an algorithm based on the Benders Decomposition, combining the Dual Dynamic Programming, was developed. Results show that the stochastic approach leads to more ro
Date
: 2026-01-18
Size
: 274kb
User
:
therealneel7
[
matlab
]
PSO
DL : 0
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.)
Date
: 2026-01-18
Size
: 5kb
User
:
安联的大球童
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