利用人工智能原理中BP神经网络算法，建立的彩票预测程序，当然不可能都预测中，但是要学习神经网络的人值得一看...

基于EKF的机器人SLAM演示程序, 对于搞机器人定位及地图构建的朋友会有一定帮助, 这个版本用的人比较多-EKF-based SLAM demo of the robot, the robot carry out positioning and mapping will have a certain friend to help, this version used by many people

Principles of Data Mining是数据挖掘领域里面又一本经典的教材，呵呵，希望对大家有帮助-Principles of Data Mining is a data mining inside another in this classic textbook, Oh, you want to help

自适应遗传算法matlab代码.自适应遗传算法的问题是很容易早熟,好处就是速度快 .不过我将在其中会引入一个早熟判定标志的，并设定一个阈值，如此以来，就可以防止早熟现象了 -Adaptive genetic algorithm Matlab code. Adaptive genetic algorithm is very easy precocious, advantage is faster. However, in which I will be introducing an early sign of determination, and set a threshold, so, you can prevent precocious phenomenon

遗传算法的c源码 说明很详细-Genetic Algorithm c Note very detailed source

是各种常用算法的集合，又递归、神经网络、遗传、枚举、排序、圆周率求解等等。是学习的好材料。-Is a collection of various commonly used algorithms and recursive, neural networks, genetic, enumeration, sorting, solving, etc. pi. Is a good learning materials.

围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.-particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.

《游戏编程中的人工智能技术》一书中10，11章源代码- Game programming in artificial intelligence technology, one source book, Chapter 10,11

这是一篇关于文本分类问题的综述，详细的介绍了文本分类的技术发展。-text category

背包问题的遗传算法解法-knapsack problem Genetic Algorithm Solution

这个软件支持Bayesian衰退和分类模形，它基于神经系统网络和Gaussian作用。它也包括一些根本的程序实现有限和无限混合的模型。-software support this recession and Bayesian classification pattern, It is based on neural network and Gaussian role. It also includes some of the procedures to achieve limited and unlimited mixed model.