VC中利用人工智能解决八迷宫问题。这是一个很有趣的人工智能小程序，不妨试试看。...

用matlab语言编写的,该程序名为模拟退火算法m 源程序-Matlab language used, the procedure called simulated annealing algorithm m source

本工具包主要是为对神经网络有兴趣人士提供的一种方便，灵活的学习和研究软件。 JNNT由java语言写成，具有跨平台的优越性能.java applet的演示版更简单到只需要任何机器上的浏览器就可以运行，无需安装任何大型附加软件。更方便爱好者通过internet远程访问资源。 支持反向传播算法(BP),LBG聚类法和径向基网络(RBF) -This toolkit is for people interested in neural networks has provided a convenient, flexible learning and research software. JNNT by the java language, cross-platform with superior performance. Java applet demo version is more simple to just any machine can run a browser, without installing any large-scale add-on software. Enthusiasts through the internet more convenient remote access to resources. To support the back-propagation algorithm (BP), LBG clustering method and radial basis function network (RBF)

支撑向量机算法的一种改进算法，是基于增量学习的算法-Support Vector Machine Algorithm an improved algorithm is based on the incremental learning algorithm

本程序是用c语言编写的基于决策树分类方法的数据挖掘算法，它对测试集进行分类，挖掘出潜在的规则-this procedure is used to prepare the language c decision tree classification based on the data mining algorithm, which tests set for classification, tapping the potential rules

这个程序是人工智能里字句归结的一个程序，它采用了线性归结策略和删除策略相结合的方法-the procedure is artificial intelligence Lane words attributed to the procedure, which uses the linear sum strategies and strategy to delete a combination of methods

遗传算法优化神经网络的C源程序- Heredity algorithm optimization nerve network C source program

MIT大学的机器学习课程讲稿,很经典的!包括分类,回归,判别式学习,产生式学习,SVM等,基本上包括常用的机器学习算法-MIT University of speech machine learning curriculum, it is classic! Including classification, regression, discriminant study, resulting in learning, SVM, etc., basically including the commonly used machine learning algorithms

This a GA implementation using binary and real coded variables. Mixed variables can be used. Constraints can also be handled. All constraints must be greater-than-equal-to type (g >= 0) and normalized (see the sample problem in prob1 in objective()).-This a GA implementation using binary and real coded variables. Mixed variables can be used. Constraints can also be handled. All constraints must be greater-than-equal-to type (g gt;= 0) and normalized (see the sample problem in prob1 in objective()).

bp神经网络模拟，是根据以立体的模拟程序-bp neural network simulation, which is based on a three-dimensional simulation program

《神经网络理论与MATLAB7实现》电子书，超星4.0格式。- Neural network theory and implementation MATLAB7 e-books, Chaoxing 4.0 format.