也是学习别人的程序，不过他没有把核心代码给我

此为疾病诊断专家系统，用这种结构建立的知识库可以很方便地实现上面所提到的各种功能。这种结 构的最独特之处就是依靠相同的关键（疾病名或其代码）来实现一种疾病与其症候之 间的相互联系。疾病名与症候分别用二叉树进行排序。排序后可由疾病名而查到与该 疾病名有关的所有详细情况，也可由一种症候而查到哪些疾病有这种症候，以及该症 候可能引起各种疾病的概率。-This is the disease diagnosis expert system, using this structure to establish the knowledge base can easily realize the above mentioned features. The structure of the most unique is that relying on the same key (the disease or its code) to achieve a disease and its symptoms between. Name and symptoms of disease were treated with binary tree sort. Sort by the disease after the name of the disease were found with all the details of which can also be a symptom of the diseases that have found such a symptom, as well as the symptoms may lead to the probability of various diseases.

与神经网络有相似的根源。但近年来在分类中得到了广泛的应用。这意味着，如果我对一些事物进行了分类（但你对我如何分类一无所知，或者说你不知道用于分类的规则），当一个新数据出现时，SVM可以预测它应该属于哪个集合。

该程序是基于MATLAB环境的pso实现tsp问题-The program is based on the MATLAB environment, the issue of PSO realize tsp

基于人工神经网络求解TSP问题的论文,很不错.-Based on artificial neural network to solve TSP problem papers, is pretty good.

这是一篇关于文本分类问题的综述，详细的介绍了文本分类的技术发展。-text category

关于神经网络方面的130个程序，采用matlab语言，比较全-On the neural network 130 procedures, the use of matlab language, compare the whole

人工免疫算法的源代码,经过调试运行,效果还不错,和大家分享!-Artificial immune algorithm source code, after debugging run, the effect is also good to share with you all!

一个用C编写的实现BP神经网络的源程序，希望大家用得上-C prepared by a BP neural network to achieve the source, I hope everyone useful

一个bp神经元网络的c++实现，优化了算法，有可执行界面-A bp neural network c++ to achieve and optimize the algorithm, there is an executable interface

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.