PID algorithm simulation program, including four bands rk algorithm.

WEKA 3-5-5 Explorer 用户指南 原中文版-Explorer how to use weka 2-5-5

这是神经网络和遗传算法想结合的c++程序，希望对需要的朋友 有所帮助。-This is a neural network and genetic algorithm would like to combine c++ Procedures, and they hope to help a friend in need.

自己用swarm开发的一个车辆跟驰的模型，希望能跟广大爱好者共同探讨。-own use development of a swarm of vehicles- following model, the majority of fans are able to explore together.

TSP问题的一个简单实验例程,应用效果不错,可以作为初学者的参考-TSP problem with a simple test routine, applications good results can be used as a reference for beginners

可以自动识别一个程序中调用的所有函数，并写入到 output.txt文件中。-can automatically identify a process called all functions, and write to output.txt document.

Matlab遗传算法工具箱函数及应用实例 Matlab遗传算法工具箱函数及应用实例-Matlab genetic algorithm toolbox function and application of genetic algorithm Matlab toolbox function and application example

vb写的改进的遗传算法程序。是一些通用代码，与具体问题对应的代码空出来，用的时候填进去。根据我的经验，要想用好遗传算法，代码必须自己写，因为问题不同，编码，杂交，变异算子可能都不一样。特别是杂交算子，需要根据问题调整，甚至创造出新的杂交方法。而且适应度计算的代码也需要自己写，特别是带约束的优化问题 -vb write improvement in the genetic algorithm. Some common code, with the specific issues the corresponding code space, and the time spent filling into account. According to my experience, in order to make good use of genetic algorithms, code must write their own, because different issues, coding, hybridization and mutation operator may not like. In particular hybrid operator, the need to adjust the problem, or even create a new hybrid method. But fitness calculation of the code required to write their own, especially with the constrained optimization problem

这个代码是用lib-svm来实现svm分类器的，简单易懂，并且有详细的注释，对于刚刚接触SVM的初学者有很大的帮助，一看就能上手，我也是新手，所以应该还是很有帮助的。-This code is used to achieve lib-svm classifier svm, easy-to-read, and detailed notes, just contact SVM for the great help for beginners, a look will be able to start, I am also a novice, so it should be or very useful.

数据挖掘中很不错的源码,一个share算法的java源程序,有极好的可读性-data mining is a good source, a share algorithm java source files, has an excellent readability

The tca package is a Matlab program that implements the tree-dependent component analysis (TCA) algorithms that extends the independent component analysis (ICA), where instead of looking for a linear transform that makes the data components independent, we are looking for components that can be best fitted in a tree structured graphical model. The TCA model can be applied in any situation where the data can be assumed to have been transformed by an unknown linear transformation.