A genetic algorithm source code can be used as learning to improve the use of wa...

用C++实现遗传算法求解TSP问题.txt-C++ for TSP

遗传算法优化神经网络结构和链接权，采用浮点数编码-Genetic algorithm neural network structure and link the right to use floating-point encoding

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.

线性神经网络应用实例-linear neural network application

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.

无先导粒子滤波器工具箱，并附带pf，kf，Ukf程序，用于跟踪估计-without leading particle filter toolbox and fringe pf, kf, Ukf procedures for tracking estimates

knn分类模式识别可用于文本挖掘和其他的识别分类,vc代码,-Commission pattern recognition can be used for classification of text mining and other identification classification, vc code,

经典的SOM人工神经网络例子源码，经测试可用，可作入门学习用-SOM classic examples of artificial neural network source code

HOPFIELD的一个经典用例，解决TSP问题，代码完整，是我自己编写的哦-HOPFILED cases with a classic, TSP solution, code integrity, I was prepared oh

FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分。在介绍FCM具体算法之前我们先介绍一些模糊集合的基本知识。-FCM algorithm is a clustering algorithm based on the division of its thinking is that it is making is divided into clusters with the greatest similarity between the object, and different similarity between the smallest cluster. Fuzzy C-means algorithm is an ordinary C-means algorithm, the general C-means algorithm for data delineation is rigid, while the FCM is a soft fuzzy partition. FCM in the introduction prior to the specific algorithm we first introduce some basic knowledge of fuzzy sets.