内核的演示和测试

本算法使用了遗传算法的方法实现了随机数的生成方法。能够比较平均得实现随机数的生成。-The algorithm uses a genetic algorithm to achieve the method of random number generator. Compared to the average achieved in the generation of random numbers.

遗传算法方法，步骤，实例。详细，有实例，很不错。-Genetic algorithm methods, steps, examples. Detail, there are examples of very good.

基于k均值聚类学习算法的rbf神经网络实现-K-means clustering-based learning algorithm of rbf neural network

基于改进SVM的特征选择，可以帮助大家认识SVM-To improve the SVM-based feature selection can help you understand the SVM

一款改进了的查询系统----北京公交车查询系统-new improved system for the Beijing-Bus Inquiry System

内附两个源代码，其中一个源代码是识别程序的，另一个是一个矩阵类库的，所以一并附上。 ~..~因为已经保存了训练好的网络权值，所以第一次使用识别程序时，可以直接运行Release目录下的可执行文件，然后对图片目录中的测试图片进行读入、识别。 当然读者也可以自行用训练样本训练网络，不过要特别注意训练样本的选择，否则可能造成识别率很低。训练样本选择的原则是，尽可能的有代表性，在训练时间不至于太长的情况下，训练样本数目尽量多。 -containing 2 source code, which is a source identification procedures, and the other is a matrix class library. So accompanied. ~ ~ .. Has been preserved because of the trained network weights, the first use of the identification procedures, can be run directly Release directory executable file, Then the catalog of tests conducted read into the picture, recognition. Certainly readers can use their own training samples training network, but special attention should be paid to the choice of training samples, Otherwise, it could cause a very low recognition rate. Training sample selection principle is that as far as possible be representative, in the training of the time not too long under the circumstances, the number of training samples as much as possible.

这个是关于遗传算法的比较完整的C语言程序，个人觉得还是比较有参考价值。-on the genetic algorithm is relatively complete C language program, individuals think it is quite a reference value.

数据挖掘各类代码:Apriori源代码全部-Various types of data mining code: Apriori all source code

神经网络lvq算法程序-neural network algorithm procedures lvq

带有QoS约束的组播路由问题是一个NP完全问题，遗传模拟退火算法是遗传算法和模拟退火算法的一种融合，可以为这类问题提供一个解决方案-With QoS constraint multicast routing problem is an NP-complete problem, genetic simulated annealing algorithm is a genetic algorithm and simulated annealing algorithm as a fusion, you can provide for such a solution