遗传算法

遗传算法程序，是用java编写的，适合学习最优化的朋友来作为参考-Genetic Algorithm is used in the preparation of java, the most suitable learning optimized reference to a friend

一种汉字模式识别的VC++源代码，里面包含了学习与识别的算法实现，识别一种汉字前，先学习几遍。识别率高，对学习与研究模式识别很有好处。方便修改。-a Chinese character pattern recognition VC source code, which contains the learning and recognition algorithm, a Chinese character recognition, first learn several times. The high recognition rate for the study and research of pattern recognition is very good. To facilitate change.

另一个遗传算法程序-Another genetic algorithm program

利用ICA变换进行人脸检测,是一种新的人脸检测方法-ICA transform the use of face detection, is a new face detection method

高性能交流伺服系统及其复合控制策略研究，浙江大学博士论文。 关键词:交流伺服系统，矢量控制，直接转矩控制，复合控制，PID控制，GA，IGA，模糊控制，切换控制，协调控制-High Performance AC Servo System and its Advanced Mixed Practical Control Strategy.Thesis of Zhejiang University. Keywords:AC servo system, Vector Control, Direct Torque Control,Combined Control, PID Control, GA, IGA, Fuzzy Control, Coordinating Control.

人工股市（Artificial Stock Market，简称ASM）是模拟股市运作的一个程序。在这个电脑中的虚拟市场中，若干被称为交易者的人工智能程序(Agent)通过观察它们所在的数字世界中股价和股息的不断变换而做出预测，并且根据这些预测做出购买股票与否以及购买股票数量的决策。反过来，所有的交易者的决策又决定了股票的价格，这样，整个的股票交易市场就构成了一个自我封闭的计算系统。同时，这些交易者都具有学习的能力，可以根据以前预测的成功或者失败对自己的决策进行调整，并且通过一种被称为遗传算法的方法产生创新能力。总之，ASM是一个电脑中不断进化的虚拟股票市场！通过研究ASM，我们可以更好的理解现实世界的行为，并且它提供了一个很好的现实股市的隐喻。 备注：该程序运行需要有Swarm平台的支持，关于这个平台可以到http://www.swarm.org免费下载。 -artificial stock market (Artificial Stock Market, or ASM) is a stock market simulation operation of the procedure. In this computer in the virtual market, a number of traders known as artificial intelligence (Agent) by observing them where the digital world and the stock dividend and the constantly changing projections, and based on these projections made whether or not to purchase stocks and the purchase of shares in decision-making. Conversely, all the decision-making transactions in turn determines the share price, so that the entire stock market would constitute a self-enclosed computer system. Moreover,

遗传算法应用-Application of genetic algorithms

通俗的介绍了RVM与SVM的区别,写的非常通俗易懂-Tutorial of RVM

分类器的设计，包括knn方法和BP的方法。对一系列样本点进行分类-Classifier design, including methods and BP KNN method. On a series of sample points to classify