前馈神经网络算法

神经网络C程序的第3章-neural network C procedures for the Chapter 3

基于BP算法的贝叶斯网络参数学习， 实现了图形话的节点表示和样本生成， 图形话的结果分析-BP algorithm based on Bayesian network parameter learning, the achievement of the graphics, then the node express and sample generation, if the results of graphical analysis

人工免疫网络,实现分类,聚类,函数寻优等功能,采用matlab编写.-artificial immune network, classification, clustering, search function Excellence function, prepared using Matlab.

人工智能8数码问题-artificial intelligence problem

遗传算法和神经网络的结合应用，通过Visual C++环境来实现该功能，使计算能力更强-Genetic algorithms and neural networks combination of applications, through the Visual C++ environment to achieve this feature, so that more computing power

最新开发的小波融合算法实现VC程序。非常好用。-latest development of the wavelet algorithm VC fusion procedures. Very handy.

小波神经网络的MATLAB程序，没有用库函数-Wavelet Neural Network MATLAB procedures, did not use library functions

Description: C4.5Rule-PANE is a rule learning method which could generate accurate and comprehensible symbolic rules, through regarding a neural network ensemble as a pre-process of a rule inducer. Reference: Z.-H. Zhou and Y. Jiang. Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble. IEEE Transactions on Information Technology in Biomedicine, 2003, vol.7, no.1, pp.37-42. 使用神经网络集成方法诊断糖尿病,肝炎,乳腺癌症的案例研究. -Description: C4.5Rule-PANE is a rule learning method which could generate accurate and comprehensible symbolic rules, through regarding a neural network ensemble as a pre-process of a rule inducer. Reference: Z.-H. Zhou and Y. Jiang. Medical diagnosis with C4.5 rule preceded by artificial neural network ensemble. IEEE Transactions on Information Technology in Biomedicine, 2003, vol.7, no.1, pp.37-42.

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

模拟退火算法经常用于最优化问题，本算法通俗易用！-Simulated annealing algorithm often used for optimization problems, this algorithm is popular to use!