Description: 经典遗传算法工具箱中的初始种群的生成程序，与大家分享-classical genetic algorithm toolbox initial population of the production process, share with you Platform: |
Size: 1024 |
Author:赵学 |
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Description: ％ [BestPop,Trace]=fmaxga(FUN,LB,UB,eranum,popsize,pcross,pmutation)
％ Finds a maximum of a function of several variables.
％ fmaxga solves problems of the form:
％ max F(X) subject to: LB <= X <= UB
％ BestPop--------最优的群体即为最优的染色体群
％ Trace----------最佳染色体所对应的目标函数值
％ FUN------------目标函数
％ LB-------------自变量下限
％ UB-------------自变量上限
％ eranum---------种群的代数,取100--1000(默认1000)
％ popsize--------每一代种群的规模；此可取50--100(默认50)
％ pcross---------交叉的概率,此概率一般取0.5--0.85之间较好(默认0.8)
％ pmutation------变异的概率,该概率一般取0.05-0.2左右较好(默认0.1)
％ options--------1×2矩阵,options(1)=0二进制编码(默认0),option(1)~=0十进制编码,option(2)设定求解精度(默认1e-4)- [BestPop, Trace] = fmaxga (FUN, LB, UB, eranum, popsize, pcross, pmutation) Finds a maximum of a function of several variables. Fmaxga solves problems of the form: max F (X) subject to : LB <= X <= UB BestPop-------- optimal chromosome groups is the best group Trace---------- chromosome corresponding to the best objective function value FUN------------ objective function LB------------- variable lower limit since the UB------------- variable upper limit eranum--------- populations algebra, take 100- 1000 (default 1000) popsize-------- population size of each generation this desirable 50- 100 (default 50) pcross--------- crossover probability, the probability of a general check 0.5- 0.85 between the better (default 0.8) pmutation------ mutation probability, the probability of 0.05 general admission better about-0.2 (default 0.1) options-------- 1 × 2 matrix, options (1) = 0 binary code (default 0), option (1) ~ = 0 decimal coding, option (2 ) set accuracy (default 1e-4) Platform: |
Size: 3072 |
Author:mmcc |
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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: 这是一道很基本的程序，一方面希望它对初学遗传算法的兄弟们有用（包含了遗传算法实现的大部分步骤，而且有详细的注释），另一方面旨在抛砖引玉，
在下浅见：
1、遗传算法在进行大规模计算时，数据交换量大，速度确实是一个瓶颈，就如这道程序，在种群规模50，进化代数1000时运行需要40秒左右(cpu:duron 1G),当然，小弟编程能力弱，望各位大侠指教啊，或帮我修改一下这道程序
-This is a very basic procedure, While they want it beginner GA brothers useful (including the genetic algorithm to achieve the most steps and a detailed note), on the other hand aims to attract the next suggestions : 1. GA conducting large-scale calculations, the data exchange capacity, speed is a bottleneck, as this practice. 50 in population size, the evolution of algebra required for the operation of 1000 when about 40 seconds (cpu : duron 1G), Of course, the younger programming weak, and hopes to enlighten ah Shanhaiguan, or help me rephrase this practice Platform: |
Size: 47104 |
Author:haozi |
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Description: logistic、malthus人模型都可以用于预测呈指数增长的数据模型，预测未来的人口的等数据，是由人口学家提出的，可用于预测未知的数目，以及检测一些模型所得结果的正确性。-logistic, malthus human model can be used to predict an exponential growth in data model, to predict the future, such as population data, is proposed by the demographer can be used to predict the number of unknown, as well as a number of model testing the correctness of the results. Platform: |
Size: 1024 |
Author:雷浩 |
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Description: ：Matlab遗传算法(GA)优4~-r-具箱是基于基本操作及终止条件、二进制和十进制相互转换等操作的综合
函数库。其实现步骤包括：通过输入及输出函数求出遗传算法主函数、初始种群的生成函数，采用选择、交叉、变异
操作求得基本遗传操作函数。以函数仿真为例，对该函数优化和GA改进，只需改写函数m文件形式即可。-: Matlab genetic algorithm (GA) U 4 ~-r-a box is based on the basic operation and termination conditions, binary and decimal conversion operation, such as a comprehensive function library. The realization of these steps include: input and output functions through the genetic algorithm to derive the main function, initial population generation function, the use of selection, crossover, mutation operation to achieve the basic function of genetic manipulation. Simulation in order to function as an example, the GA function optimization and improvement, just rewritten m the form of a document can function. Platform: |
Size: 117760 |
Author:icyrock |
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Description: 一个关于拟合预测的程序,从以往的人口数目预测以后的人口数目-A prediction on the fitting procedure, from the previous population after population prediction Platform: |
Size: 2048 |
Author:小珍 |
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Description: 此程序包是用双种群蚁群算法来求中国75个城市的最短路径问题，即典型的TSP问题，把包解压运行main.m文件即可-This package is a dual population of ant colony algorithm to seek China s 75 cities, the shortest path problem, that is typical TSP problem, the package can extract the files to run main.m Platform: |
Size: 8192 |
Author:梁锦兆 |
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Description: 混沌模型logistc映射程序，描述昆虫变化的经典数学模型——虫口模型-Chaos Model logistc mapping procedures, changes in the classic description of insects mathematical model- Population Model Platform: |
Size: 1024 |
Author:yanshulei |
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Description: matlab遗传算法工具箱函数及实例讲解1
核心函数： 初始种群的生成函数 -matlab genetic algorithm toolbox and examples of function on one core function: the initial population of the generating function Platform: |
Size: 1024 |
Author:xjk |
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Description: bp神经网络在人口预测上的应用，可以根据前几年的人口数值预测出以后的人口数值-bp neural network prediction in the population on the application, based on previous years, the population of numerical prediction of the future value of the population Platform: |
Size: 7168 |
Author:杨卓 |
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Description: 财政收入预测模型源码：财政收入与国民收入、工业总产值、农业总产值、总人口、就业人口、固定资产投资等因素有关。根据列表的多年原始数据，构造预测模型进行预测。-Revenue forecasting model source: Financial income and national income, industrial output, agricultural output, the total population, working population, investment in fixed assets and other factors. According to the list of multi-year raw data, prediction models constructed to predict. Platform: |
Size: 8192 |
Author:列子 |
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Description: maltab遗传算法源程序，此程序为一个一个的小程序分开的，很完整。包括编码，设定初始种群，交叉，变异，及结束条件等-maltab genetic algorithm source code, this procedure a small as a separate process, it is complete. Including encoding, set the initial population, crossover and mutation, and the end conditions Platform: |
Size: 7168 |
Author:joean |
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Description: Particle swarm optimization (PSO) is a population based stochastic optimization technique developed by Dr. Eberhart and Dr. Kennedy in 1995, inspired by social behavior of bird flocking or fish schooling. Each particle keeps track of its coordinates in the problem space which are associated with the best solution (fitness) it has achieved so far. (The fitness value is also stored.)
This value is called pbest. Another "best" value that is tracked by the particle swarm optimizer is the best value, obtained so far by any particle in the neighbors of the particle. This location is called lbest. when a particle takes all the population as its topological neighbors, the best value is a global best and is called gbest. Following is the steps of PSO:
Platform: |
Size: 1024 |
Author:BBB |
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Description: 用来构建人类人口增长的模型，主要反映时间与人口数量之间的关系，以及人口增长率与时间之间的关系(The model used to construct the human population growth mainly reflects the relationship between time and population, and the relationship between population growth rate and time) Platform: |
Size: 1024 |
Author:王克贤
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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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Description: Matlab 遗传算法(Genetic Algorithm)优化工具箱是基于基本操作及终止条件、二进制和十进制相互转换等操作的综合函数库。其实现步骤包括：通过输入及输出函数求出遗传算法主函数、初始种群的生成函数，采用选择、交叉、变异操作求得基本遗传操作函数。以函数仿真为例，对该函数优化和GA 改进，只需改写函数m 文件形式即可。(The Matlab Genetic Algorithm optimization toolbox is a comprehensive function library based on basic operations and termination conditions, binary and decimal conversion and other operations. The implementation steps include: the main function of genetic algorithm and the generation function of the initial population are obtained by the input and output functions, and the basic genetic operation function is obtained by the selection, crossover and mutation operations. Taking function simulation as an example, the function optimization and GA improvement only need to rewrite function m file form) Platform: |
Size: 9216 |
Author:FZenjoys |
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Search - population matlab