人工智能编程示例

本程序是用java语言编写的数据挖掘分类算法中的决策树分类方法c4.5程序代码-this procedure is used java language classification of data mining algorithms decision tree classification code Bank

这是关于数据仓库与数据挖掘的Apriori算法的实现程序，基于关系型数据库的。-This is the implementation of Apriori Algorithm used in Data Warehouse and Data Mining filed, based on the Relation Database.

LM编程算法，在神经网络中有很大应用之处，神经网络源代码,及BP网络训练界面,其中的L-M算法非常实用 -LM programming algorithm, in a large neural network applications, the neural network source code, and the BP network training interface, in which the LM algorithm is very practical

人工智能经典问题TSP问题的C语言实现，内含源程序和调试过程生成的文件-AI classic TSP"s C language, and includes source code debugging process produces files

基于Hopfield人工神经网路的室内全域路径优化。主要是利用Hopfield求解TSP的方法。用于课程设计。-based on artificial neural network Hopfield indoor entire domain path optimization. Hopfield is mainly used for TSP method. For course design.

这是目前网上所能找到的最全面的adaboost的C++算法，但是需要自己训练的数据-This is the Internet can find the most comprehensive adaboost C algorithms, However, it needs its own training data

自己编的遗传算法同BP神经网络结合的代码！并且在神经网络模型上进行多目标寻优，结果有doc文档详细说明！实现BP-GA多目标优化应用实例！-Own genetic algorithm with BP neural network combined with the code! And in the neural network model for multi-objective optimization, the result document has a detailed description doc! Realize BP-GA multi-objective optimization application examples!

人工神经网络神经网络的程序和训练数据 解压缩后可以运行的-ANN neural network training procedures and decompress data after the run

语音信号处理工具包,里面提供了很多有用的操作。这是最新版本-voice signal processing tool kit containing a lot of useful operation. This is the latest version

cost存放了一个强连通图的边权矩阵，作为一个实例。 可在workspace中加载 运用此算法要注意多次试验。 bianquan.m文件给出了一个参数实例，可在命令窗口中输入bianquan,得到邻接矩阵C和节点个数N以及一个任意给出的路径R,，回车后再输入jiaohuan3,得到了最优解。 由于没有经过大量的实验，又是近似算法，对于网络比较复杂的情况，可以尝试多运行几次jiaohuan3,看是否能到进一步的优化结果。-storage cost of a strongly connected graph edge weight matrix, as an example. Can be loaded in the workspace to use this algorithm to the attention of numerous tests. bianquan.m document gives examples of a parameter can be in the command window, type bianquan, be the adjacency matrix C and the node number N and an arbitrary given path R,, carriage return after the input jiaohuan3, have been the optimal solution . After the absence of a large number of experiments, it is approximate algorithm, for more complex network situations, you can try to run several jiaohuan3, can look to further optimize the results.