Description: A hybrid Particle Swarm Optimization algorithm for finding the minimum of
the function fitness in the real space.-Particle Swarm Optimization algo abbreviation for finding the minimum of the function fi tness in the real space. Platform: |
Size: 2048 |
Author:chen |
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Description: A program to demonstrate the optimization process of particle swarm optimization. A two-dimensional objective function is visualized by level of grey: the lighter the color, the higher the function value. The particles are shown as red circles, their trajectory as red lines.-A program to demonstrate the optimization process of particle swarm optimization. A two- dimensional objective function is visualized by level of gray : the lighter the color, the higher the value function. The particles ar e shown as red circles. their trajectory as red lines. Platform: |
Size: 12288 |
Author:无心 |
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Description: 基于matlab的基本粒子群优化算法，可应用与最优潮流计算等-Matlab-based optimization of the particle swarm algorithm can be applied with optimal power flow calculation Platform: |
Size: 2048 |
Author:milan |
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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Eberhar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。
-Particle Swarm Optimization (PSO) is an evolutionary computation technique (evolutionary computation), and has Eberhar Dr. Dr. kennedy invention. Stems from the behavior of predatory birds, PSO with genetic algorithm is similar to an iterative optimization-based tools. Platform: |
Size: 2048 |
Author:叶开 |
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Description: 基于粒子群和微分进化的优化算法研究,是一篇优秀的博士论文，希望能对大家有用-Based on particle swarm optimization and differential evolution algorithm, is an excellent doctoral thesis, hoping to be useful for all of us Platform: |
Size: 1819648 |
Author:chenjy |
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Description: A dissipative particle swarm optimization is
developed according to the self-organization of dissipative
structure. The negative entropy is introduced to construct an
opening dissipative system that is far-from-equilibrium so as to
driving the irreversible evolution process with better fitness.
The testing of two multimodal functions indicates it improves
the performance effectively.
structure. The negative entropy is introduced to construct an
opening dissipative system that is far-from-equilibrium so as to
driving the irreversible evolution process with better fitness.
The testing of two multimodal functions indicates it improves
the performance effectively.-A dissipative particle swarm optimization isdeveloped according to the self-organization of dissipativestructure. The negative entropy is introduced to construct anopening dissipative system that is far-from-equilibrium so as todriving the irreversible evolution process with better fitness.The testing of two multimodal functions indicates it improvesthe performance effectively.structure. The negative entropy is introduced to construct anopening dissipative system that is far-from-equilibrium so as todriving the irreversible evolution process with better fitness.The testing of two multimodal functions indicates it improvesthe performance effectively. Platform: |
Size: 5950464 |
Author:sky |
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Description: Swarm intelligence algorithms are based on natural
behaviors. Particle swarm optimization (PSO) is a
stochastic search and optimization tool. Changes in the
PSO parameters, namely the inertia weight and the
cognitive and social acceleration constants, affect the
performance of the search process. This paper presents a
novel method to dynamically change the values of these
parameters during the search. Adaptive critic design
(ACD) has been applied for dynamically changing the
values of the PSO parameters.-Swarm intelligence algorithms are based on naturalbehaviors. Particle swarm optimization (PSO) is astochastic search and optimization tool. Changes in thePSO parameters, namely the inertia weight and thecognitive and social acceleration constants, affect theperformance of the search process. This paper presents anovel method to dynamically change the values of theseparameters during the search. Adaptive critic design (ACD) has been applied for dynamically changing thevalues of the PSO parameters. Platform: |
Size: 365568 |
Author:sky |
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Description: 一种带有灰色关联方法的粒子群算法，主要是用于多目标优化或多目标决策-A method of gray correlation with particle swarm optimization, is mainly used for multi-objective optimization or multi-objective decision-making Platform: |
Size: 4096 |
Author:毛毛 |
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Description: 应用协同微粒群算法对一个4-6-1形式的神经网络进行离线训练.-Application of Cooperative Particle Swarm Optimization for a 4-6-1 form of neural network off-line training. Platform: |
Size: 3072 |
Author:duyanli |
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Description: 耗散粒子群（DPSO）优化算法C程序及其测试实例-Dissipative Particle Swarm (DPSO) optimization algorithm C program and its test case Platform: |
Size: 8192 |
Author:Cheng bing |
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Description: 粒子群算法的实例，应用于无线网络节点的动态布署等。图和表显示结果-Examples of particle swarm optimization applied to the wireless network nodes, such as dynamic deployment. Graph and table shows the results of Platform: |
Size: 4096 |
Author:QGP |
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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: ％程序名称：求解约束优化问题的改进粒子群优化算法
％程序功能：求解带各种约束条件的优化问题
％输入条件：各种初始条件，以及设定参数
％输出数值：最优解位置以及函数极小值
- Program name: for solving constrained optimization problems to improve particle swarm optimization algorithm program features: solving with a variety of constraints optimization problem input conditions: a variety of initial conditions, and the setting of parameters output values: the location of the optimal solution, as well as function of the minimum Platform: |
Size: 4096 |
Author:依然 |
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Description: 这是一个很好用的求解TSP问题的粒子群算法，很适合初学者。-This is a very good solution of TSP used in the particle swarm optimization problems, it is suitable for beginners. Platform: |
Size: 2048 |
Author:zhaogang |
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Description: 多阈值图像分类的粒子群优化算法，采用自然方法来提高优化速度和计算量-Multi-threshold image classification of the particle swarm optimization algorithm, using natural methods to improve the optimization speed and computation Platform: |
Size: 2048 |
Author:baiyilieren |
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Description: 用于分析带约束问题的输出结果,加上约束的粒子群算法功能有很大改善-Used to analyze the problem with constraint output, coupled with constrained particle swarm optimization function has greatly improved Platform: |
Size: 2048 |
Author:jiangzhiling |
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Search - particle swarm optimization