matlab编写的遗传算法，采用二进制编码，有说明文档。

利用遗传算法搜索函数最优解的c++源程序 -use of genetic algorithm search function to the optimum solution c source

把libsvm包在一起，只要能读入矩阵转换成所需的格式libsvm就可以运行了

程序演示的是用简单遗传算法随机一个种群，然后根据所给的交叉率，变异率，世代数计算最大适应度所在的代数-Program demonstrates that the simple genetic algorithm with a random population, then according to the crossover rate, mutation rate, calculating the maximum number of generations where the fitness of algebraic

文中设计了一个3层径向基神经网络(RBFN)用于对企业的5项评价指标进行聚类分析，并与蚁群算法做了比较分析。RBFN由输入层 到隐含层采用传统的K一均值算法，隐含层到输出层通过“模2递减”学习速率的BP学习；蚁群算法根据信息素的分配能够自动调整收索 路径，从而达到数据自动聚类的目的。结果表明，与蚁群算法相比，改进RBFN具有快速收敛、自动识别奇异样本的优点，而蚁群算法 无须教师学习，并能够达到全局最优。-In this paper, we designed a 3-layer RBF neural network (RBFN) for the 5-to-business evaluation indicators cluster analysis and ant colony algorithm has done a comparative analysis. RBFN from input layer to hidden layer using the traditional K-means algorithm, hidden layer to output layer through the Mode 2 decreasing learning rate of BP learning ant colony algorithm based on pheromone can automatically adjust the allocation of land Faso path, thereby to achieve the purpose of automatic data clustering. The results showed that compared with the ant colony algorithm to improve the RBFN has a fast convergence, automatic identification of singular advantage of the sample, while the ant colony algorithm do not need teachers to learn and be able to reach the global optimum.

Kohonen网络的学习过程可描述为：对于每一个网络的输入，只调整一部分权值，使权向量更接近或更偏离输入矢量，这一调整过程就是竞争学习。随着不断的学习过程，所有输入矢量都在输入矢量空间相互分离，形成了各自代表输入空间的一类模式，这就是Kohonen网络的特征自动识别的聚类功能。请解压缩后按照readme提示进行操作。-Kohonen network learning process can be described as follows : for each one network input, only part of adjusting the weights, weight vector closer to or further from the input vector, the adjustment process is competitive learning. With the continuous process of learning, all the input vector in the importation of vector space separate form their own representatives importation of a type of space, and this is a Kohonen network of automatic clustering functions. Please decompress after readme according to instructions.

神经网络模式识别及其实现，第八章。 内含：KMEANS 、KOHONEN 、LVQ 、SOFM 算法。-pattern recognition and neural network to achieve, Chapter VIII. Intron : KMEANS, KOHONEN, LVQ, SOFM algorithm.

c++实现基于神经网络的空间大战，可以学习到如何利用神经网络进行游戏编程。-c++ implementation of space war based on neural networks can learn how to play games using neural network programming.

《生物信息学》现在模式识别应用的一个重要方向。希望可以给大家有点作用！- Bioinformatics is an important direction of pattern recognition applications. Wish to give you a little Role!

遗传算法求解TSP问题-genetic algorithm for TSP

weka 的决策树的实现,对数据挖掘感兴趣的可以下哦,很好的呀-if you like Dataming