我根据书上算法自编的蚁群程序，也是我的中期筛选设计。目录下函数收敛图是用了VC的结果，在matlab里画的...

这是一个的遗传算法程序,开发平台是vc7.0-This is a genetic algorithm process, the development platform is vc7.0

遗传算法 算法实例MATLAB程序，包括了：选择 变异 交叉 遗传算子-GA

The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application.-The software implements particle filteri Vi and Rao Blackwellised particle filtering az r conditionally Gaussian Models. The RB algori thm can be interpreted as an efficient stochast ic mixture of Kalman filters. The software also includes efficient state-of-the-art resampl ing routines. These are generic and suitable az r any application.

模式识别实例工程的源代码-example source code

一种基于家庭进行选择的遗传算法VC++源程序，经测试其性能优于一般算法和自适应算法。-a family to choose the genetic algorithm source VC, After testing its performance is superior to the general algorithms and adaptive algorithm.

贝叶斯算法是基于贝叶斯定理 P(H|X) = P(X|H)P(H) / P(X).。对于多属性的数据集，计算 P(X|Ci) 的开销非常大，为减低计算复杂度，我们做条件独立的假设，即给定元组的类标号，假定属性值有条件地相互独立，即在属性间不存在依赖关系。此程序仅为算法的一个实现，根据训练数据训练分类器-Bayesian algorithm is based on the Bayes theorem P (H | X) = P (X | H) P (H)/P (X).. For multi-attribute data sets, computing P (X | Ci) of the overhead is very large, in order to reduce the computational complexity, we do conditional independence assumption that a given tuple class label, it is assumed that property values conditionally independent of each other, that does not exist in the inter-attribute dependencies. This procedure is only an implementation of algorithm, according to training data classifier training

神经网络C程序的第8章-neural network C procedures for the Chapter 8

利用一个较为成熟的遗传算法基础类库（作者:刘康），我自己在做论文的时候写得一个关于利用遗传算法进行节点部署应用的实验程序。您可以很容易地在其基础上实现自己应用相关的算法程序，进行研究验证工作。希望此源码能够为相关人事提供帮助。-Use of a more mature class library based on genetic algorithm (Authors: Liu Kang), I have to do when writing a thesis on the use of genetic algorithm application node deployment Experimental procedures. You can easily realize in their own applications based on the algorithm-related procedures, conduct research validation. I hope that this source can provide assistance for the relevant personnel.

自适应共振神经网络可以实现自动学习与分类具有自适应的功能-adaptive resonance neural network can automatically learning and classification of adaptive function

首先采用某种编码方式将解空间映射到编码空间，每个编码对应问题的一个解，称为染色体或个体。一般通过随机方法确定起始的一群个体，称为种群，在种群中根据适应值或某种竞争机制选择个体，使用各种遗传操作算子产生下一代如此进化下去，直到满足期望的终止条件。-begin using some form of coding mapping to the solution space coding space, each encoding a corresponding solution to the problem, known as chromosome or individual. General randomly determined by the initial group of individuals, called stocks, the stocks based on fitness or some mechanism to choose the individual competition, the use of genetic Operator evolution of the next generation so on, until the termination meet expectations conditions.