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...

讲述关联规则在零售业中的作用,相应的算法和实例实现-on association rules in the retail sector"s role, the corresponding algorithm to achieve and examples, etc.

this is a program about TSP -this is a program about TSP

文件中包含某老师关于智能优化计算课程中的遗传算法部分的讲义，其中包含详细的例子及源代码。-File contains a calculation of the teachers on the intelligent optimization of the genetic algorithm curriculum part of the lecture, which includes detailed examples and source code.

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一个基本遗传算法的C++语言实现，有三个文件构成。-A basic genetic algorithm C++ Language, there are three files.

国外的一个A*算法演示，带源代码。作为算法参考非常好-abroad an A* algorithm demonstration, with the source code. As a very good reference algorithm

字符识别系统——利用双重用途分类后的神经网络系统对原始字符进行识别编码

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,

改进遗传算法在TSP中的应用!很好用哦!-Improved Genetic Algorithm in TSP application! Good use Oh!

he algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.