解非线性规划模型的遗传算法，采用visual c++语言编写，结构清晰，明了易懂，注释完整...

NSGA-II遗传算法的文档，里面的内容比较好理解，是学习遗传算法的必备知识-Genetic Algorithm NSGA-II of the document, which is better understanding of the content is a genetic algorithm to learn the knowledge necessary

这是有关于人工神经网络的应用主要是应用到股票价格的分析与预测-This is on the application of artificial neural network is applied to the stock price analysis and prediction

模糊K近邻分类器，模式识别和机器学习经常要使用的一个分类器-K neighbor fuzzy classifier, pattern recognition and machine learning are often used in a classifier

此程序用于测试神经元的库函数 // 它展示了怎样用这个库所生成的多层BP网络来求解宇称问题-this procedure for testing neuronal function of the library// it tells how to use this library generated by the multi-storey BP network to solve problems Parity

遗传算法 算法实例MATLAB程序，包括了：选择 变异 交叉 遗传算子-GA

基于GA的BP改进算法，用遗传算法对BP 神经网络算法进行改进试用过 里面有数据是可以使用的-GA-based improvement of BP algorithm, genetic algorithm with BP neural network algorithm tried there are data that can be used

use genetic ant algorithm to slove TSP problem-use genetic algorithm to slove ant TSP ty B"Tselem,

（其中已经包含5个源码）所附源程序C或C++代码文件及其可执行文件 Scs.cpp 基本分类算法源程序， 输入数据文件cfile.txt,efile.txt,gfile.txt,pfile.txt ,rfile.txt,tfile.txt Sga.c 基本遗传算法源程序, 输入数据文件input，输出文件output A_life.c 基于遗传算法的人工生命模拟源程序, 输入数据文件world GA_nn.c 基于遗传算法优化神经网络结构源程序,输入数据文件sample Patmat.c 基于遗传算法提取基元图形源程序-(which includes five OSS) attached to C or C source code files and executable files Scs.c pp basic classification algorithm source files, input data files cfile.txt, efile.txt. gfile.txt, pfile.txt, rfile.txt. tfile.txt Sga.c basic genetic algorithm source files, input data files input, output file output A_life.c based on genetic algorithm simulation source Artificial Life, import data files GA_nn.c world based on genetic algorithm optimization neural network structure source, import data files Patmat.c sample extraction based on genetic algorithm-based graphic source yuan

《遗传算法理论应用与软件实现》中的选择MATLAB源代码-"Genetic Algorithm Theory and Application Software" option MATLAB source code

一种基本的模式识别方法，进行了部分改进，简单实用，采用matlab仿真，经编译后无误。供大家学习参考-A basic pattern recognition methods, partially improved, simple and practical, the use of matlab simulation, as compiled correctly. Reference for everyone to learn