搜索资源列表
speedyGAv1.3.zip
- 一种快速简单的遗传算法程序,基于Matlab7,加入特殊的交叉算子和变异算子,使算法更快。,SpeedyGA is a vectorized implementation of a genetic algorithm in the Matlab programming language.SpeedyGA has been created and tested under Matlab 7 (R14). Added mutation and crossover mask pregeneration
psowithdate
- %--- 名称:带交叉因子的改进PSO算法 %------功能:求解多维无约束优化问题 %------特点:收敛性强,还可以加入变异算子 ---- Name: with cross-factor function to improve the PSO algorithm------: Solving multi-dimensional unconstrained optimization problems------ characteristics: strong convergen
A Comparison of Crossover and Mutation in Genetic
- 遗传算法的文章- Heredity algorithm article
MK
- 气象上常用的检验突变的一个程序,也叫做MK算法 值需要添加文件路径,可直接运行-Weather on the commonly used mutation testing a procedure, also known as MK algorithm will need to add the file path value can be directly run
mutation
- 遗传算法的变异操作的源代码-Mutation operation of genetic algorithm source code
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
ga1
- 遗传算法程序说明: fga.m 为遗传算法的主程序 采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-Descr iption of the procedures for genetic algorithms: fga.m main program for the genetic algorithm using binary Gray encoding, roulette wheel based on the law of non-line
mutation
- matlab 的一些实例,希望对大家有所帮助,多多参考-reference no no no no no no no no no
CMOBPSO
- OPSOCM: Opposition based PSO with Cauchy Mutation.
yichuansuanfa_jixieshou
- 提出一种改进的遗传算法用于求解机械手运动学逆问题. 该算法采用实数编码, 其交叉概率和变异 概率根据解的适应度函数值自适应调整. 计算机仿真结果显示, 该算法较简单遗传算法(SGA) 求解精度高, 收敛速度快且稳定性能好.-An improved genetic algorithm for solving the inverse problem of manipulator kinematics. The algorithm uses real number encoding, the
psoMB
- this code written for solve a sample test function by pso based on mutation.
Mutation_of_the_PSO
- 引入变异算子的PSO,希望对大家的学习研究有所帮助。-Mutation of the PSO, we hope to help the study of learning.
Simple-genetic-algorithm-source-code
- 这是一个非常简单的遗传算法源代码,是由Denis Cormier (North Carolina State University)开发的,Sita S.Raghavan (University of North Carolina at Charlotte)修正。代码保证尽可能少,实际上也不必查错。对一特定的应用修正此代码,用户只需改变常数的定义并且定义“评价函数”即可。注意代码 的设计是求最大值,其中的目标函数只能取正值;且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂
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.
MutationTesting
- A simple mutation testing based mini project handout
cauy_guassian
- Cauchy mutation based on guassian particle swarm optimization
Immunity-clone-algorithm-with-mutation-coevolution
- 利用免疫系统的克隆选择机制,提出一种用于函数优化的算法. 算法的主要特点是:在迭代过程中,不仅抗体得到进化,同时建立变异向量集,令变异向量同步进化,协同工作,达到优化的目的. 仿真实验表明,所提出的算法能以较快的速度完成给定范围的搜索和全局优化任务-By using the clonal selection echanism of the immune system , a method for function optimizing is proposed. The character of
Particle-algorithm
- 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。 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
function crossover mutation selection
- use crossover, mutation, selection
function crossover mutation &selection
- 利用matlab实现种群的选择,交叉,变异等功能(realize of selection, mutation and crossover)