Description: 简单遗传算法经典例子!! SGPC: Simple Genetic Programming in C by Walter Alden Tackett and Aviram Carmi-simple genetic algorithm classic example! ! SGPC : Simple Genetic Programming in C by Walter Alden Tackett and Aviram Carmi Platform: |
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Author:潘峰 |
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Description: 基于基本遗传算法的函数最优化SGA.C
A Function Optimizer using Simple Genetic Algorithm developed from the Pascal SGA code presented by David E.Goldberg-based on the basic genetic algorithm optimization function SGA.C A Optimize Function r using Simple Genetic Algorithm developed fro m Pascal SGA the code presented by David E. Goldb erg Platform: |
Size: 636928 |
Author:J.Chen |
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Description: 用JAVA写的遗传算法的例子,比较简单,如果解压缩的时候需要密码的话,应该是“1”。写的比较简单。是老早以前写的了。-using Java to write the genetic algorithm example, relatively simple, if decompression time requires a password, then it should be "one." The relatively simple to write. Before long ago was written in the past. Platform: |
Size: 9216 |
Author:许江东 |
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Description: 这是一个非常简单的遗传算法源代码,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、单点杂交和均匀变异。如果用 Gaussian变异替换均匀变异,可能得到更好的效果。代码没有任何图形,甚至也没有屏幕输出,主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu, 目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’;系统产生的输出文件为‘galog.txt’。输入的 文件由几行组成:数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界,第二行为第二个变量提供上下界,等等。 -This is a very simple genetic algorithm source code, code guarantees minimal, in fact there is no need Checking. For a specific application to amend this code, users only need to change the constant definition and the definition of "evaluation function" can. Attention to the design of the code for the maximum, the objective function can only take positive; and function and adapt to the individual was no difference between the value. The system uses ratio choices, the essence model, single point of hybridization and mutation uniform. If Gaussian variation replacement uniform variation, may be a better result. Code no graphics, or even no screen output, mainly to ensure that the platforms to the high portability. Readers can get ftp.uncc.edu. Contents coe/evol prog.c the document Platform: |
Size: 3072 |
Author: |
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Description: A Function Optimizer using Simple Genetic Algorithm developed from the Pascal SGA code presented by David E.Goldberg-A Function Optimizer using Simple Genetic Algorithm developed from the Pascal SGA code pr esented by David E. Goldberg Platform: |
Size: 5120 |
Author:刘振兴 |
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Description: GA(Simple Genetic Algorithm)是一种强大的智能多变量优化算法,它模仿种群繁殖规律来进行优化。
本SGA可以优化变量,求最小值,最大值(当把函数倒数也就求最小值啦)
并且支持浮点编码,grey编码,二进制编码;轮赌法选择,锦标赛选择;单点交叉,均布交叉,浮点交叉;单点变异,浮点变异;-GA (Simple Genetic Algorithm) is a powerful, intelligent multi-variable optimization algorithms, which mimic the breeding populations of the law to be optimized. SGA can optimize this variable, and the minimum value, maximum value (when the function of the countdown you will seek the minimum value) and to support the floating-point encoding, grey code, binary code round of gambling options, tournament selection single-point crossover, uniform Cross, floating-point crossover single point mutation, floating-point variation Platform: |
Size: 9216 |
Author:yuandi |
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Description: 一个java编写的简单遗传算法,我从网上下的,感谢源码提供者-Java prepared by a simple genetic algorithm, I am under from the Internet, thanks to the provider source Platform: |
Size: 4096 |
Author:Jean |
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Description: */
/* A Function Optimizer using Simple Genetic Algorithm */
/* developed from the Pascal SGA code presented by David E.Goldberg */
/* 同济大学计算机系 王小平 2000年5月 -*//* A Function Optimizer using Simple Genetic Algorithm*//* developed from the Pascal SGA code presented by David E. Goldberg*//* Department of Computer Science, Tongji University in May 2000 WANG Xiao-ping Platform: |
Size: 5120 |
Author:刘璐 |
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Description: 简单的遗传算法源代码,挺实用的,大家可以借鉴-Simple genetic algorithm source code, very useful, we can learn from Platform: |
Size: 2048 |
Author:asdfasdf |
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Description: This a simple genetic algorithm implementation where the evaluation function takes positive values only and the fitness of an individual is the same as the value of the objective function Platform: |
Size: 3072 |
Author:梁民 |
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Description: 简单的遗传算法源程序,你可以运行及参考,初步掌握遗传算法的过程-Simple genetic algorithm source code, you can run and reference, the initial grasp the process of genetic algorithm Platform: |
Size: 6144 |
Author:Anni |
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Description: 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、单点杂交和均匀变异。如果用Gaussian变异替换均匀变异,可能得到更好的效果。代码没有任何图形,甚至也没有屏幕输出,主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu,目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’;系统产生的输出文件为‘galog.txt’。输入的文件由几行组成:数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界,第二行为第二个变量提供上下界,等等。
-This is a very simple genetic algorithm source code, by Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) as amended. Code to ensure that as little as possible, in fact, do not have errors. The application of a specific amendment to this code, the user can change the definition of constants and the definition of "evaluation function" can be. Note the code is designed for maximum value, in which the objective function can only take positive and function to adapt to individual values and there was no difference between values. The system uses the ratio of choice, the best model, a single point of hybridization and uniform mutation. If the variation of the replacement of uniform Gaussian mutation may be more effective. Code without any graphics, or even no screen output, mainly to ensure a high portability between platforms. Readers can ftp.uncc.edu, directory coe/evol documents obtained prog.c. Asked to enter the fi Platform: |
Size: 4096 |
Author:Kaavield |
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Description: 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、单点杂交和均匀变异。如果用 Gaussian变异替换均匀变异,可能得到更好的效果。代码没有任何图形,甚至也没有屏幕输出,主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu, 目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’;系统产生的输出文件为‘galog.txt’。输入的 文件由几行组成:数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界,第二行为第二个变量提供上下界,等等。 -It is a very simple genetic algorithm source code, is Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) amendment. Code to ensure as little as possible, in fact, do not have to troubleshooting. The application of a specific amendment to this code, the user simply changes the definition of constants and the definition of "evaluation function" can be. Note that the code is designed to seek maximum value, in which the objective function can only take positive and the function value and the individual is no difference between the fitness value. The system uses the rate selection, the essence of model, single-point crossover and uniform mutation. If you replace the uniform mutation with Gaussian mutation, may be more effective. Code without any graphic or even no screen output, mainly to ensure a high portability between platforms. Readers can ftp.uncc.edu, directory coe/evol file prog.c obtained. Required input file sho Platform: |
Size: 8192 |
Author:李礼 |
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Description: 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。-This is a very simple genetic algorithm source code, by Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) amendment. Platform: |
Size: 4096 |
Author:lulu |
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