the C language, BP artificial intelligence algorithms can be seen teaching

MCRGSA------组播路由问题遗传模拟退火算法 ％M-----------遗传算法进化代数 ％N-----------种群规模，取偶数 ％Pm----------变异概率调节参数 ％K-----------同一温度下状态跳转次数 ％t0----------初始温度 ％alpha-------降温系数 ％beta--------浓度均衡系数 ％ROUTES------备选路径集 ％Num---------到各节点的备选路径数目 ％Cost--------费用邻接矩阵 ％Source------源节点标号 ％End---------目的节点标号组成的向量 ％MBR---------各代最优路径编码-MCRGSA------ Multicast Routing genetic simulated annealing% M----------- genetic algorithm algebra% N----------- population size, even take Pm----------% probability parameter variation%----------- same temperature K Jump under a number of state----------% t0 initial temperature cooling% alpha------- beta coefficient%-------- balanced concentration coefficient% ROUTES------ Alternative Path Set% Enable--------- nodes to the number of alternative paths%-------- Cost adjacent costs Matrix% Source------ source node labeling% End--------- destination node labeling Group Vector%% of the MBR--------- generations optimal path coding

该软件通过BP神经网络学习机制，能够对屏幕上的数字进行识别。-the software through BP neural network learning mechanism, to right on the screen digital identification.

这是一种利用神经网络来进行人脸识别的算法。-This is a neural network to the face recognition algorithm.

基于VC开发的遗传算法源程序，有详尽的注释说明-based on the development of the VC genetic algorithm source files, a detailed Explanatory notes

网络能通过学习带正确答案的实例集自动提取“合理的”求解规则，即具有自学习能力-network can learn the correct answer with examples of automatic drawing of the "reasonable" solution rules, that is self-learning ability

BP算法实现异或问题,采用S型函数的前向多层神经网络及其逆推学习算法-BP algorithm differences or problems, use of the S-Function to the multilayer neural networks and learning algorithms Backstepping

bp神经网络的工具包-bp neural network tool kit

用于三分类的BP算法程序,matlab源码-three classifications for the BP algorithm procedures, Matlab FOSS

可以基于遗传算法的网络故障知识获取技术，大学时候老师留的作业自己编的-be based on genetic algorithm network fault access to knowledge, when the teacher left the University of operating their own series

This directory contains code implementing the K-means algorithm. Source codemay be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANSprogram accepts input consisting of vectors and calculates the givennumber of cluster centers using the K-means algorithm. Output isdirected to the screen.