关联规则中的频繁项集生成算法TreeMiner，可在linux和windows下编译运行。...

遗传算法的一些应用-GA applications

Neural Networks ，8种神经网络，BP，RBF，CPN等通过VC++来实现了！-Neural Networks, 8 Neuro network, BP, RBF, CPN, such as through VC++ To achieve!

蚁群遗传算法的实现，VC++源代码！蚁 群遗传算法的实现，VC++源代码！蚁群遗传算法的实现，VC++源代码！-Ant Colony Genetic Algorithm, VC++ Source code! Ant Colony Genetic Algorithm, VC++ Source code! Ant Colony Genetic Algorithm, VC++ Source code!

一个关于BP网络的设计，实现一个函数的逼近，了解关于MATLAB神经网络工具箱的应用。-On the design of BP network, the realization of a function approaches, learn more about the MATLAB neural network toolbox applications.

基于肤色和模板的人脸检测MATLAB源代码.rar具有一定参考价值。-and template based on the color of face detection MATLAB source. Rar certain reference value.

遗传算法解决NN逼近任意函数-genetic algorithm to solve arbitrary function approximation NN

FCM算法的实现及测试，该源码实现常用数据集的测试。-FCM algorithm and testing, the achievement of the source data sets commonly used test.

一个自主机器人的电力传输线检查可引起电压的输电线路作为电源来源提出。该机器人采用电流互感器的主要促使目前从输电线路和远见功能浏览。结果表明，该机器人可以 自动沿着输电线路。-An autonomous robot for the power transmission line inspection that can induce the voltage from the transmission line as a power source is presented. The robot uses current transformer principal to induce the current from power transmission line and vision function to navigate. The results have shown that the robot can automatically move along the power transmission line.

本文采用红外光电传感器技术, 建立了一个基于神经网络的客流计数系统, 与传 统的仅利用光电传感器计数方法相比, 该方法提高了实时客流计数准确率。为了更好的分 类识别计数, 针对采集的连续的时空序列客流数据特点, 改进了已有的分割方法和针对客 流实际情况的特征提取方法。最后经过稀疏和密集客流模拟仿真测试, 结果表明, 本文所 提出的模型能够识别多人并排的情况, 误差率较低, 具有理论和实际意义。-RBF

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