搜索资源列表
Multi-objective-search-algorithm
- 基于粒子群算法的多目标搜索算法，基于matlab仿真源程序代码，用于学习matlab算法设计的一个很好的例子-Multi-objective search algorithm based on particle swarm optimization algorithm, based on the Matlab simulation source code for a good example to learn matlab algorithm design
power-system-problem-based-on-PSO
- 利用粒子位置和速度的改变更新，在熟悉多目标粒子群算法的基础上利用测试函数对该算法进行仿真，并对仿真结果进行优化。-The particle position and velocity changes update in the familiar multi-objective particle swarm optimization based on the use of test functions to simulate the algorithm, and the optimization
PSO
- 这是粒子群优化算法的实现，求解多模态函数非常使用-This is the Particle Swarm Optimization algorithm to solve multi-modal function is the use of
GS_CH_PSO1.1_discrete1.0_2007830
- 基于粒子群优化与灰色系统理论的多目标优化程序，很好用-Based on Particle Swarm Optimization and gray system theory of multi-objective optimization process, a very good use
Multiagent_Systems_and_Distributed_AI
- 介绍分布式人工智能的不错的入门书籍，主要利用分布式人工智能技术来构建multi－agent系统-Distributed artificial intelligence good introduction introductory books, the main use of distributed artificial intelligence technologies to build multi-agent system ... ...
mopsoPDF
- 有关多目标粒子群算法的论文，想研究多目标的可以参考-Of the multi-objective particle swarm optimization of the papers, I would like to research objectives can refer to
opt4j-2.0
- Java平台的启发式优化算法，包含了多目标进化算法（SPEA2和NSGA2），多目标差异进化，PSO和单目标模拟退火算法。并且包含了ZDT,DTLZ和WFG等测试函数-Opt4J is a framework for applying meta-heuristic optimization algorithms to arbitrary optimization problems. The Opt4J framework currently includes a multi-obje
shili
- 基于改进粒子群算法的多目标最优潮流计算 基于改进粒子群算法的多目标最优潮流计算-Particle Swarm Optimization Based on Improved Multi-objective Optimal Power Flow
multi-ctp1
- 一个基于阈值的粒子比较准则，用于处理多目标约束优化问题,该准则可以保留一部分序值较小且约束违反度在允许范围内的不可行解微粒,从而达到由不可行解向可行解进化的目的；一个新的拥挤度函数,使得位于稀疏区域和Pareto前沿边界附近的点有较大的拥挤度函数值,从而被选择上的概率也较大 从而构成解决多目标约束优化问题的混合粒子群算法。-A comparison based on the threshold criteria for the particle to handle multi-objective
particle-swarm-optimization
- 应用于求解多目标最优解的粒子群算法的MATLAB程序-Applied to solve multi-objective optimal solutions of the MATLAB program PSO
QPSO
- 量子粒子群优化算法，采用matlab编程，可实现快速优化多维函数，不易陷入局部最优值-Quantum particle swarm optimization algorithm, using matlab programming, multi-dimensional functions can be optimized for fast, easy to fall into local optimal value
pso_threshold-segmentation
- 图像阈值分割，为确定图像分割的最佳阈值，基于粒子群优化算法提出了一种多阈值图像分割方法-Image segmentation, image segmentation to determine the optimal threshold value, based on particle swarm optimization algorithm proposes a multi-threshold image segmentation
Multi-Agent-Particle-Swarm-Algorithm
- 结合多智能体的学习、协调策略及粒子群算法，提出了一种基于多智能体粒子群优化的配电网络重构方法。该方法采用粒子群算法的拓扑结构来构建多智能体的体系结构，在多智能体系统中，每一个粒子作为一个智能体，通过与邻域的智能体竞争、合作。能够更快、更精确地收敛到全局最优解。粒子的更新规则减少了算法不可行解的产生，提高了算法效率。实验结果表明，该方法具有很高的搜索效率和寻优性能。-Combining the study of multi-agent technology，coordinating strateg
Multi-objective-particle-swarm
- 多目标粒子群优化算法 多目标粒子群优化算法 多目标粒子群优化-Multi-objective particle swarm optimizationMulti-objective particle swarm optimizationMulti-objective particle swarm optimization
DMS-PSO_code
- 动态多群粒子群代码-基于J.J.Liang2005年得文章-dynamic multi-swarm optimizer
Particle-Swarm
- 基于Pareto支配的多目标粒子群算法程序，用matlab设计实现，已经通过多个公认测试函数测试，结果良好。 -Based on multi-objective particle swarm algorithm Pareto domination, using matlab design implementation, test function has been recognized by a number of tests with good results.
MGAA
- 本算法是基于遗传算法的多种群算法，能够对全局的多个目标进行同时寻优，在全局中能够取得较好的全局最优值。-This is a multi-swarm algorithm based on genetic algorithm, capable of multiple targets simultaneously global optimization, in the big picture can achieve better global optimum.
Multi-objective-particle-swarm
- 利用matlab编写的多目标粒子群算法可以很快得到最优值。-Use matlab write multi-objective particle swarm algorithm can quickly obtain optimal value.
Codes-of-BSA-and-CSO
- Chicken Swarm Optimization（CSO）鸡群优化算法，2014年提出的群智能优化算法。 Bird Swarm Algorithm（BSA）鸟群算法，2015年最新的群智能优化算法。 作为两种全新的群智能优化算法，CSO和BSA都具有简单，良好扩展性的特点，是天然的多种群算法！ http://cn.mathworks.com/matlabcentral/profile/authors/3317597-xian-bing-meng 有关算法信息，可在上述网站查询
particle-swarm-algorithm
- 该资料为多目标粒子群求优MATLAB代码。改进的多目标粒子群算法，包括多个测试函数 对程序中的部分参数进行修改将更好地求解某些函数-The data is a multi object particle swarm optimization MATLAB code. The improved multi-objective particle swarm optimization algorithm, including the number of test functions in the pr