用mathlab编写的经典的模拟退火应用程序，包括图着色问题，最大截问题等...

基于神经网络的乒乓球机器人乒乓球轨迹预测代码，神经网络的参数可能有待进一步改进-code of PingPong Robot trajectory predicting based on neural network

详细介绍了SVM 和RVM的区别及各自的优点，说明RVM在很多方面优于SVM-Described in detail the difference between SVM and the RVM and their respective advantages, indicating RVM in many ways superior to SVM

Particle Swarm Optimization (PSO) for the TSP

多目标优化问题，此例中经遗传算法优化子代个体数目逐步减少，最后稳定在10个染色体个体-Multi-objective optimization problem, in this case, by the genetic algorithm to gradually reduce the number of offspring individuals, and finally stabilized at 10 chromosome individual

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,

一种新型模糊形态神经网络及其应用研究,比较有参考意义-fuzzy form a new neural network and its applied research, more reference value

ArcObject的空间查询代码，比较简单和初步的供大家一起学习-The spatial query ArcObject code is relatively simple and everyone together for a preliminary study

一个利用C#语言实现的遗传算法源程序-a C# language of the genetic algorithm source

现代控制理论经典PPT，非常有效，而且方便好用-Classic modern control theory, PPT, very effective and convenient easy to use

神经网络算法程序，对数学建模的同学很有用处。谢谢大家喜欢。-Neural network algorithm procedures, mathematical modeling of the students very useful. Thank you all like it.