搜索资源列表
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粒子群算法滤波器，用粒子群算法实现了LP滤波器-Particle swarm algorithm filter, particle swarm algorithm with the LP filter
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This an implementation of Particle Swarm Optimization algorithm using
the same syntax as the Genetic Algorithm Toolbox, with some additional
options specific to PSO. Allows code-reusability when trying different
population-based optimization al
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comparison with the genetic algorithm, the advantages of PSO is simple
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Global Optimization Toolbox provides methods that search for global solutions to problems that contain multiple
maxima or minima. It includes global search, multistart, pattern search, genetic algorithm, and simulated
annealing solvers. You can u
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另一个粒子群优化算法工具箱，具有与遗传算法工具箱相同的语法结构。-Implementation of a PSO algorithm with the same syntax as the Genetic Algorithm Toolbox.
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用matlab编写的遗传算法加上粒子群算法，求解最优配置问题的程序-Prepared by the genetic algorithm with matlab with PSO, the optimal configuration problem solving process
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Parsopoulos等采用罚函数法，利用非固定多段映射函数对约束优化问题进行转化，再利用PSO算法求解转化后问题，仿真结果显示PSO算法相对遗传算法更具有优越性，但其罚函数的设计过于复杂，不利于求解；Hu等采用可行解保留政策处理约束，即一方面更新存储中所有粒子时仅保留可行解，另一方面在初始化阶段所有粒子均从可行解空间取值，然而初始可行解空间对于许多问题是很难确定的；Ray等提出了具有多层信息共享策略的粒子群原理来处理约束，根据约束矩阵采用多层Pareto排序机制来产生优良粒子，进而用一些优良的
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this algorithm is hybrid PSO algorithm with Genetic algorithm
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It is hybrid pso .In this pso algorithm combined with genetic algorithm
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GA遗传算法与PSO离子群组合算法matlab程序，以下是使用本程序的简单介绍与使用步骤
1）修改设计变量个数
NPar变量定义的是设计变量个数，本例为8，使用时需根据自己实际情况进行修改。
2）修改设计变量的上下限
VarLow 与VarHign定义的是设计变量的上下限，使用时需根据自己实际情况进行修改。记住，变量的维数，要与1）变量个数一致哦。
3）修改FunName
变量FunName定义的是优化目标函数值的计算函数，根据自己实际情况改成自己的函数名。
4）修改
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Genetic algorithm developed with PSO
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matlab code for 2 area system with pid controller and thisnwill compares genetic algorith and pso algorithm
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粒子群算法求解多维约束函数极值，并与遗传算法比较。结果发现，粒子群有很好的精度。-A particle swarm optimization algorithm for solving the extreme value of multi dimensional constrained function, and compared with genetic algorithm. The results show that the particle swarm has a good accurac
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this code describe combine pso algorithm with genetic algorithm
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genetic and iwo algorithm in matlab with binary method
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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, P
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将改进的粒子群算法和GA与SVM相结合，通过参数寻优构建新模型完成对空气质量指数的预测(The improved particle swarm optimization and genetic algorithm are combined with SVM. The prediction of air quality index (AQI) is completed by constructing a new model by parameter optimization.)
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本算法为用遗传算法改进粒子群GA-PSO算法，附带含有程序使用说明。(This algorithm uses genetic algorithm to improve particle swarm optimization GA-PSO algorithm, with instructions for the use of the program.)
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该算法中将速度位移公式与遗传算法相结合用于结果解决多配送中心的路径优化问题(In this algorithm, the velocity displacement formula is combined with the genetic algorithm to solve the path optimization problem of multiple distribution centers)
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