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3GA_NN
- Simple Genetic Algorithm 遗传算法的!c语言的源程序.-Simple Genetic Algorithm GA! C language of the source.
GA-1_cpp
- 神经网络算法用CPP描述，在数学建模中会有应用-Neural network algorithm described by CPP
GA
- Visual Studio 2008 Csharp project which contains a library with an implementation of the Genetic Algorithm and a test project which demonstrates its use
ga
- 本压缩包内收集了一些C#常用的7种遗传算法，这些算法主要是保存超个体的基本遗传算法、仿生双倍体遗传算法、人工双倍体遗传算法、保存历史最优解的遗传算法、保存历史最优解的仿生双倍体遗传算法等，另外，对随机数的产生机制进行了优化，在内层循环中也能产生高质量的随机数。部分功能可通过源码爱好者测试截图中看出，这里不再详述。-The compression bag to collect some C# commonly used seven kinds of genetic algorithms is pr
GA
- 基于免疫遗传算法的QOS路由选择问题 给予免疫遗传算法的多目标优化问题 -Immune genetic algorithm based QOS routing problems provide the immune genetic algorithm for multi objective optimization problem
GA
- An introduction to Genetic Algorithm Slides
thirdbuttons
- 类是由 StronglyTypedResourceBuilder // 类通过类似于 ResGen 或 Visual Studio 的工具自动生成的。 // 若要添加或移除成员，请编辑 .ResX 文件，然后重新运行 ResGen-GA aLGORITHM
GA-bp(CPP)
- GA Algorithm optimize the bp neural network
fast-GA-program
- 提供了快速遗传算法源程序及基本原理，广大学者免费学习-Provides a quick genetic algorithm source code and the basic principles, the majority of scholars free learning
GA-TSP
- 利用遗传算法求解30个城市的旅行商（tsp)问题，C++程序-Genetic Algorithm for TSP (tsp) problem C++ program
ga
- 遗传算法程序代码，包括函数最优化，基本算法，分层遗传改进算法等-Genetic algorithm code, including function optimization, the basic algorithm, hierarchical genetic algorithm to improve
ga-tsp
- 用遗传算法解决TSP问题，和AFORGE.d-genetic algorithm to solve TSP with C#
C
- 基于C语言的简单遗传算法源程序，希望大家指正，看看有没有错误-Simple genetic algorithm (ga) based on C language source code, hope everyone correction, see if there are any mistakes
GeneticAlgorithm
- AI - Simple Genetic Algorithm (GA) to solve a card problem-Introduction This article describes how to solve a logic problem using a Genetic Algorithm. It assumes no prior knowledge of GAs. In fact, half of this article is dedicated to explaining th
GA
- 这是我们课程学习用的遗传算法代码，用C语言写的，有关于函数优化的，也有关于TSP问题的，资料很好，与大家一起分享-This is our course to learn genetic algorithm code, written in C language, on the function optimization, but also on the TSP problem, the information is very good, to share with you