Description: VC++编写的简单遗传算法，非常经典，值得下载。-VC prepared by the simple genetic algorithm, very classic, it is worth the download. Platform: |
Size: 59870 |
Author:沈建峰 |
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Description: VC++编写的简单遗传算法，非常经典，值得下载。-VC prepared by the simple genetic algorithm, very classic, it is worth the download. Platform: |
Size: 59392 |
Author:沈建峰 |
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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: 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: VC++编写的遗传算法，值得下载,压缩包解压时没有密码。--VC prepared by the simple genetic algorithm, very classic, it is worth the download. Platform: |
Size: 7168 |
Author:张勇 |
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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: 几个简单的遗传算法例子，一般有点相关基础的都能看懂，很容易的。-Few simple examples of the genetic algorithm, based on the general correlation can understand a little bit, very easy. Platform: |
Size: 7168 |
Author:胡中友 |
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Description: 一个简单的遗传算法在c#。它将不会多线程,也有异国情调的操作人员和收敛标准(例如一种情形发现许多解决方法是非常相似的)。它只是证明遗传算法在托管代码,利用的一些特点。net的运行时间。
-A simple genetic algorithm in c#. It will not be multi-threaded, there are also exotic operators and convergence criteria (for example, found that many solutions to a situation is very similar.) It just proved that genetic algorithm in managed code, the use of some of the features. net running time. Platform: |
Size: 39936 |
Author:zsepy |
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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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Description: This a simple genetic algorithm program for finding minimizers of a function. I wrote this in 1999 when I was interested in aerodynamic optimization problems. I think that genetic algorithm is a very interesting optimization algorithm.-This is a simple genetic algorithm program for finding minimizers of a function. I wrote this in 1999 when I was interested in aerodynamic optimization problems. I think that genetic algorithm is a very interesting optimization algorithm. Platform: |
Size: 4096 |
Author:cdp |
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Description: 简单函数优化的遗传算法程序，非常全面，可以在数学建模大赛中使用-Simple function optimization of genetic algorithm procedures, very full Platform: |
Size: 4096 |
Author:章鱼 |
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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 is developed by Denis Cormier (North Carolina State University), Sita S.Raghavan (University of North Carolina at Charlotte) correction. . Platform: |
Size: 12288 |
Author:王兴杰 |
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Description: Matlab实现遗传算法的文档介绍，虽然简单，但是对初学者思路上的提点有很好的作用。-Matlab document describes the genetic algorithm, though simple, but there is a very good role in reminding beginners ideas. Platform: |
Size: 291840 |
Author:林天 |
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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) corrected. Code to ensure as little as possible, in fact, do not have to troubleshoot. For a specific application fix this code, users only need to change the definition of constants and the definition of "evaluation function" button. Note that the code is designed for the maximum, in which the objective function can only take positive values , and fitness function values and the individual is no difference between the values . The system uses the ratio selection, the essence of the model, a single point crossover and uniform mutation. If you replace the uniform mutation with Gaussian mutation may get better results. Code has no graphics, or even no screen output, mainly to ensure high portability between platforms. Readers can ftp.uncc.edu, catalog coe/evol files prog.c ge Platform: |
Size: 35840 |
Author:周成 |
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Description: 本程序详细讲解了关于遗传算法的优化问题，对于学习遗传算法帮助很大-This procedure gave a detailed account on the genetic algorithm optimization problems, very helpful for learning genetic algorithm Platform: |
Size: 4096 |
Author:李晨晨 |
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Description: 另一种遗传算法C语言编程方法，也是很简易常用的方法 -Another genetic algorithm C language programming method, and also is very simple and commonly used method
Platform: |
Size: 9216 |
Author:Chen |
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Search - genetic algorithm very simple