遗传算法的经典之作

用于m=2 的机器调度问题，可求出最优解与花费的时间-m = 2 for the machine scheduling problems, the optimal solution can be obtained with the time

convert a matrix to a libsvm format [class1 char1 char2 ... charN class2 char1 char2 ... charN]

用matlab仿真的递推极大似然法辨识程序，可用来进行系统辨识，很好用-simulation using Matlab Recursive maximum likelihood method identification procedures, which can be used for system identification, good use

这是一个很好的关于BP神经网络的程序,用于两类数据的分类.-This is a very good network of BP procedures for the two types of data classification.

图像检测模板匹配的Visual C++代码-Image Detection template matching Visual C code

遗传免疫是算法的程序 大家可以看看 遗传免疫算法 我也是刚开始学 传上去大家共同学习-Genetic immunization is a method of procedure we will look at the genetic immune algorithm I am also just beginning to learn Chuan-up of common learning

本程序实现了一个人工神经网络的算法，相关领域的人可以参考。-This procedure implements a neural network algorithm, in related fields who can refer to.

粒子群算法的示例程序，不错。可用来进行函数优化、神经网络训练等。-PSO algorithm sample program, yes. Available for function optimization, neural network training.

FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分。在介绍FCM具体算法之前我们先介绍一些模糊集合的基本知识。-FCM algorithm is a clustering algorithm based on the division of its thinking is that it is making is divided into clusters with the greatest similarity between the object, and different similarity between the smallest cluster. Fuzzy C-means algorithm is an ordinary C-means algorithm, the general C-means algorithm for data delineation is rigid, while the FCM is a soft fuzzy partition. FCM in the introduction prior to the specific algorithm we first introduce some basic knowledge of fuzzy sets.

介绍了遗传算法的基本原理和求解流程, 详细阐述了Matlab 遗传算法工具箱的使用方法, 并通过使用遗传算法工具箱对一个典型的函数优化问题进行求解, 验证了该工具箱在解决函数优化问题上的有效性和实用性。-Introduce a genetic algorithm to solve the basic principle and flow in detail Matlab genetic algorithm toolbox to use, and by using genetic algorithm toolbox for a typical function optimization problems to solve, the validity of the toolbox in solving function optimization problems on the effectiveness and practicality.