搜索资源列表
PSOGA
- 改进的群体智能算法，简称PSO算法，包括C和matlab两种版本
PSOGA
- 带交叉因子的改进PSO算功能：求解多维无约束优化问题收敛性强，还可以加入变异算子-With cross-factor improvement of PSO operator functions: Solving multi-dimensional unconstrained optimization problem of strong convergence can also add mutation operator
xiaoshengjingyichuansuanfa
- 利用改进的小生境遗传算法来编程，适合对这方面感兴趣的人员研究-The use of improved niche genetic algorithm is used to programming, suitable for persons interested in research in this area
PSOGA
- PSO和GA的结合算法，对PSO中效果较差的粒子进行交叉和变异操作。-The combination of PSO and GA algorithm, PSO particles in the less effective cross and mutation.
PSOGA
- 带交叉因子的粒子群遗传算法，寻找最优位置-Particle Swarm with cross-factor genetic algorithm to find the optimal position
psoga
- 粒子群算法混合遗传算法代码，经过本人修改，方便实用。-Particle swarm optimization hybrid genetic algorithm code, after I modify, convenient and practical.
psoga
- 采用PSO和GA算法优化RBP神经网络的参数-PSO and GA algorithm optimization using neural network parameters RBP
PSOGA
- PSO_GA allgorithem matlab m-file
PSOGA
- 求解多维无约束优化问题,收敛性强，还可以加入变异算子-Multidimensional problem solving unconstrained optimization, convergence and strong, you can also join the mutation operator
PSO-GA-TSP-PID
- 压缩包包括5个群智能算法的程序，即PSOGA-PID优化，PSO的多目标perota优化问题，基于TSP-PSO算法，遗传算法求解TSP问题，遗传算法求解TSP问题-Compression package includes five swarm intelligence algorithm procedures, namely PSOGA-PID optimization, PSO perota multi-objective optimization problem, TSP-PSO algo
psoga
- 基于遗传算法的改进PSO算法，重点在于详细描述了遗传算法的交叉及变异操作，为新手提供最基本的编译思路。-Improved genetic algorithm based on PSO algorithm, the focus is a detailed descr iption of the genetic algorithm crossover and mutation operation for novices to provide the basic idea to compile.
GAPSO-PSOGA
- how to mix Genetic Algorithm And Particles Swarm Optimization
PSOGA
- 这是PSO算法和GA算法联合使用的matlab程序，用于数据定量分析-This is the algorithm of PSO and GA used in conjunction matlab program for quantitative analysis of data
psoga
- 用遗传算法和粒子群算法实现对函数的最大值的寻找，并且比较两者算法的性能好坏，通过运行时间，迭代次数等来判断-The genetic algorithm and particle swarm algorithm are used to find the maximum value of the function, and the performance of the two algorithms is compared. The running time and the number of ite
PSOGS
- particle swarm optimization genetic algorithm combined
PSOGA
- 粒子群优化算法，弥补pso全局搜能力差，GA局部搜索能力差的不足(Particle Swarm Optimization (PSO) can make up for the deficiencies of poor global search ability of PSO and poor local search ability of GA.)