神经网络vc源代码神经网络的VC++代码呀

包括883分酒问题，图的遍历等人工智能基本算法-Including 883 hours of liquor problem, artificial intelligence, such as graph traversal algorithm

这是一个用vb写的TS算法，可以提供初学者尝试

遗传算法的C语言计算，同时以文本的方式输出和图形的方式输出。-genetic algorithm in C language, while the text and graphic output of the output.

关联规则的频繁项集算法bomo的源代码，含说明文件，C编写，可在linux和windows下编译。-Related and regular frequent source codes which collects algorithm bomo, includes the supporting paper, C is written, can compile under linux and windows

遗传算法应用-Application of genetic algorithms

三维人脸动画的合成：利用数据挖掘和语音驱动（解决了语音和动画的同步）-3D Facial Animation Synthesis : Using Data Mining and voice-driven (to solve the voice and animation simultaneously)

运用神经网络的方法先将数据分类分析,然后再将未知类归类-The use of neural network analysis of data classification methods first, and then classify the unknown category

这是我自己编的从数据中自动提取模糊规则的程序,这个文件中包括了一个主程序和几个函数,能够自动提起模糊规则、合并优化模糊规则。-This is my own series of the data from the automatic extraction of fuzzy rules procedures, the document includes a main program and several function, can automatically initiate fuzzy rules, merging optimization fuzzy rules.

k中心点 编制和调试一个程序，它将用户输入的正规式转换为以状态图和矩阵形式表示的确定有穷自动机。 1．把正规式转换为NFA 2．将NFA确定化为DFA • ＃作为正规式的终止符 • 考虑复合正规式 • 开始状态号为0 -focal point for the preparation of k and debug a program, it will the user to enter the formal conversion to a state diagram and matrix forms express the determination of DFA. 1. The formal type is converted to NFA2. Will determine the NFA into a DFA

本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。 具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006. -I prepared by incremental random neural network algorithm, which is characterized by the largest approximation properties can be guaranteed, and fast good results can be used as an academic comparison and analysis. The current benchmark is only suitable for the regression problem. Specific effects may refer G.-B. Huang, L. Chen and C.-K. Siew,