函数的遗传算法优化程序

可以用C++语言开发各种神经网络：BP，RBF，HOP~…………，使用前请看看说明文档，然后建立一个自己的项目文件，只要能明白作者的思路就能很方便地进行各种神经网络的设计，本人现在就在一个系统中使用它，目前这个开发包的版本已进入0.7了，但功能差不多，本人认为0.5这个版本用着也很方便，所以把他发来，大家共享。-C language can be used to develop a variety of neural networks : BP, RBF, HOP ~ ... ... please look at the use of pre-documented, and then the establishment of a project document, you will be able to understand the author"s ideas will be very convenient for the various neural network design, I in a system in which to use it, the current version of the development kit has entered 0.7, but the function almost, I think that this version of 0.5 is also very convenient, so he made to share.

基本遗传算法源程序（基于基本遗传算法的函数最优化C程序）-Basic genetic algorithm source code (based on a function of the basic genetic algorithm optimization procedure C)

C++ Neural Networks and Fuzzy Logic -C++ Neural Networks and Fuzzy Logic

几篇关于混合遗传算法方面的好文章。-few mixed genetic algorithm on the excellent article.

经典的BPN人工神经网络例子源码 ，很经典的-BPN classic examples of artificial neural network source code, it is classic

BP小波神经网络快速学习算法研究and 小波神经网络程序-BP wavelet neural network learning algorithm for rapid research and wavelet neural network procedures

基于梯度训练方法的rbf神经网络实现，采用随机训练及测试数据-Gradient-based training methods of rbf neural network, using a random training and test data

支持向量机完整版（SVM）可以用来进行设别训练-Full version of support vector machine (SVM) can be used to set up other training

人工神经网络- Artificial nerve network

本人编写的GramSchmidt神经网络算法，和传统的神经网络算法比较，该算法能自动产生神经元，节约时间，速度快！ 本人还加了自动产生分类的方法和适合各种函数的转换，该zip包括两个文件，一个是GramSchmidt正交分解，是个子函数，主函数是orth_GramSchmidt，放在同一目录下，就可运行，可以对benchmark的逼近和分类问题提供解决方案-I prepared GramSchmidt neural network algorithm, and the traditional neural network algorithm, the algorithm can automatically generate neurons, saving time, fast! I also added a method of automatically generated classification and conversion for a variety of functions, the zip includes two documents, one is GramSchmidt orthogonal decomposition is a sub-function, the main function is orth_GramSchmidt, on the same directory, you can run can benchmark approximation and classification problems to provide solutions