Description: matlab编写的遗传算法，采用二进制编码，有说明文档。-Matlab prepared by the genetic algorithm, using the binary coding, documentation. Platform: |
Size: 106272 |
Author:张露 |
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Description: matlab编写的遗传算法，采用二进制编码，有说明文档。-Matlab prepared by the genetic algorithm, using the binary coding, documentation. Platform: |
Size: 106496 |
Author:张露 |
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Description: 该程序利用遗传算法求Rosenbrock函数的极大值。该算法主要包括确定决策变量、建立优化模型、确定编码方法、确定解码方法、确定个体评价方法、设计遗传算子、确定遗传算法的运行参数等七个步骤。-the procedures for the use of genetic algorithms Rosenbrock function of great value. The algorithm including the identification of the main decision variables, the optimal model to determine coding method to determine decoding, determine individual evaluation methods, genetic operator, genetic algorithm to determine the operating parameters seven steps. Platform: |
Size: 1024 |
Author:周龙 |
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Description: MCRGSA------组播路由问题遗传模拟退火算法
％M-----------遗传算法进化代数
％N-----------种群规模，取偶数
％Pm----------变异概率调节参数
％K-----------同一温度下状态跳转次数
％t0----------初始温度
％alpha-------降温系数
％beta--------浓度均衡系数
％ROUTES------备选路径集
％Num---------到各节点的备选路径数目
％Cost--------费用邻接矩阵
％Source------源节点标号
％End---------目的节点标号组成的向量
％MBR---------各代最优路径编码-MCRGSA------ Multicast Routing genetic simulated annealing% M----------- genetic algorithm algebra% N----------- population size, even take Pm----------% probability parameter variation%----------- same temperature K Jump under a number of state----------% t0 initial temperature cooling% alpha------- beta coefficient%-------- balanced concentration coefficient% ROUTES------ Alternative Path Set% Enable--------- nodes to the number of alternative paths%-------- Cost adjacent costs Matrix% Source------ source node labeling% End--------- destination node labeling Group Vector%% of the MBR--------- generations optimal path coding Platform: |
Size: 1024 |
Author:程爱华 |
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Description: 雷英杰的matlab遗传算法工具箱及应用,内有很多实例的编码-LEI Yingjie of Matlab Toolbox and the Genetic Algorithm application, there are many examples of coding Platform: |
Size: 9703424 |
Author:xn |
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Description: 我自己的遗传算法工具箱，支持多种编码和交叉变异操作，需要的请自行下载-my own genetic algorithm toolbox, which supports multiple coding and cross- mutation, the need to please download Platform: |
Size: 8192 |
Author:张扬 |
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Description: 基本遗传算法的matlab源程序，bstr2rval.m为基本编码转为实际值子函数，createPop.m创建初始种群子函数，crossOper.m基因交叉子函数，indiEval.m个体实际值子函数，mutateOper.m基因变异子函数，selectOper.m选择算子子函数，sga.m基本遗传算法子函数-The basic genetic algorithm matlab source, bstr2rval.m as the basic coding to the actual value of Functions, createPop.m create initial population Functions, crossOper.m gene cross-Functions, indiEval.m individual actual value Functions, mutateOper. m gene mutation Functions, selectOper.m selection operator Functions, sga.m basic genetic algorithm Functions Platform: |
Size: 4096 |
Author:闫安心 |
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Description: matlab 遗传算法GA，粒子群算法PSO,蚁群算法AS
前段时间上智能计算方法实验课上，自己做的程序。帖到这里，希望有人能改进它们，交流经验这样更有价值。
遗传算法解决最小生成树问题，PURFER编码。
粒子群算法做无约束最优化问题。
蚁群算法解决TSP问题。
如果有宝贵经验希望能交流一下，谢谢，-matlab genetic algorithm GA, particle swarm optimization PSO, ant colony algorithm for calculation of AS some time ago on the intelligent test classes, make their own procedures. Quote here, hope someone can improve them, and exchange of experience which is more valuable. Genetic algorithm to solve the minimum spanning tree problem, PURFER coding. Particle swarm optimization to do unconstrained optimization problem. Ant colony algorithm to solve the TSP problem. If there is hope to exchange our experience, thank you, He He Platform: |
Size: 5120 |
Author:stephen |
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Description: matlab 遗传算法GA，粒子群算法PSO,蚁群算法AS
前段时间上智能计算方法实验课上，自己做的程序。帖到这里，希望有人能改进它们，交流经验这样更有价值。
遗传算法解决最小生成树问题，PURFER编码。
粒子群算法做无约束最优化问题。
蚁群算法解决TSP问题。
如果有宝贵经验希望能交流一下，谢谢，-matlab genetic algorithm GA, particle swarm optimization PSO, ant colony algorithm for calculation of AS some time ago on the intelligent test classes, make their own procedures. Quote here, hope someone can improve them, and exchange of experience which is more valuable. Genetic algorithm to solve the minimum spanning tree problem, PURFER coding. Particle swarm optimization to do unconstrained optimization problem. Ant colony algorithm to solve the TSP problem. If there is hope to exchange our experience, thank you, He He Platform: |
Size: 14336 |
Author:stephen |
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Description: 语音信号的LPC线性预测编码程序，求其基因周期的源程序了，分帧，预处理，LPC算法-LPC Linear Predictive speech signal coding process, seeking the source of its genetic cycle, and sub-frame, pre, LPC algorithm Platform: |
Size: 2048 |
Author:david |
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Description: 求解双层规划问题常用的算法有极点算法、直接搜索法、下降法和非数值优化方法(如模拟退火算法、遗传算法等)，遗传算法的求解思路是：首先对上层的决策变量编码，代人下层规划模型，通过求解下层模型的决策变量值，代入上层模型计算适应度值，然后进行交叉、变异、选择操作，最后求出最优解。-Solving Bilevel Programming Problems with pole algorithm commonly used algorithms, direct search method, descent and non-numerical optimization methods (such as simulated annealing, genetic algorithms, etc.), genetic algorithm for solving approaches: the first on the top of the decision variable coding, on behalf of the were lower programming model, by solving the lower model of decision variables values into the upper model on behalf of the fitness value, and then crossover and mutation, select Options, and finally get the best solution. Platform: |
Size: 2048 |
Author:大海 |
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Description: its the matlab coding for pattern recoganization in image processing using genetic algorithm-its the matlab coding for pattern recoganization in image processing using genetic algorithm Platform: |
Size: 224256 |
Author:suresh |
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Description: 关于遗传算法的matlab实例，包括编码、交叉等操作，涉及Sheffield大学Matlab遗传算法工具箱的相关函数-Genetic algorithm Matlab examples, including coding, cross and other operations involving the correlation function of the University of Sheffield Matlab genetic algorithm toolbox Platform: |
Size: 1024 |
Author:海伦 |
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Description: 遗传算法的基本步骤如下：
1）在一定编码方案下，随机产生一个初始种群；
2）用相应的解码方法，将编码后的个体转换成问
题空间的决策变量，并求得个体的适应值；
3）按照个体适应值的大小，从种群中选出适应值
较大的一些个体构成交配池；
4）由交叉和变异这两个遗传算子对交配池中的
个体进行操作，并形成新一代的种群；
5）反复执行步骤2-4，直至满足收敛判据为止。(The basic steps of the genetic algorithm are as follows:
1) under certain coding schemes, an initial population is randomly generated;
2) use the corresponding decoding method to convert the encoded individuals into questions
The decision variable of the problem space is obtained and the fitness value of the individual is obtained;
3) according to the size of individual fitness, the fitness is selected from the population
Larger individuals constitute mating pools;
4) by crossover and mutation, these two genetic operators are pairs of mating pools
Individuals operate and form a new generation of populations;
5) repeat step 2-4 until the convergence criterion is satisfied.) Platform: |
Size: 76800 |
Author:傲视天下
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