利用小波函数做神经网络的激活函数 这是一个简单的方法在使用BP网络的时候 可以直接调用小波函数...

介绍了遗传算法工具箱及其具体的应用，很有参考价值.-introduced a genetic algorithm toolbox and its specific application of great reference value.

这里有一个用vc写的人工智能八数码源代码，，非常有参考价值，感兴趣的或者是需要的人可以来下载哦~-Here is a use of artificial intelligence was vc eight digital source code, and very useful, or is interested in need can be downloaded from Oh!

该文件是包含了机器人足球比赛中的整个系统的代码，包括动作，视觉，定位和决策-The document includes a robot soccer competition of the entire system code, including action, vision, positioning and decision-making

计算机网络经典算法：生产者与消费者问题的源代码-classic algorithm of computer network:producer and consumer

遗传算法优化神经网络结构和链接权，采用浮点数编码-Genetic algorithm neural network structure and link the right to use floating-point encoding

一个很强的利用遗传算法实现的winform sudoku 游戏-a strong genetic algorithm to achieve the winform Sudoku game

这是一个我自己编写的JAVA程序，可以运行的。思想是将KMEANS和神经网络结合起来实现模式的分类。-This is a Java program writen by meself which can be run.The chief concept is to combine KMEANS and NN to achieve classification of pattens.

神 经 网 络 的 资 料-neural network data

基本蚂蚁算法及其改进算法求解NP问题的论文汇总，而且全是中文，对于初学者一定有帮助-The basic ant algorithm and its improved algorithm for solving NP problems summary papers, and they are all Chinese, will certainly be helpful for beginners

模拟退火算法 模拟退火算法(Simulated Annealing,简称SA算法)是模拟加热熔化的金属的退火过程，来寻找全局最优解的有效方法之一。 模拟退火的基本思想和步骤如下： 设S＝{s1,s2,…,sn}为所有可能的状态所构成的集合， f：S―R为非负代价函数，即优化问题抽象如下： 寻找s*∈S，使得f(s*)＝min f(si) 任意si∈S （1）给定一较高初始温度T，随机产生初始状态S （2）按一定方式，对当前状态作随机扰动，产生一个新的状态S’ S’＝S＋sign(η).δ 其中δ为给定的步长， η为[－1,1]的随机数-simulated annealing algorithm (Simulated Annealing, or SA algorithm) is a simulation of heating molten metal in the annealing process, to find the global optimum one of the effective ways. Simulated Annealing basic ideas and the steps are as follows : S = (s1, s2, ..., sn) for all possible state posed by the pool, f : S-R non-negative cost function, that is abstract optimization problems are as follows : Find S* s, making f (s*) = min f (si) arbitrary si S (1) to set a higher initial temperature T, randomly generated initial state S (2) of a certain form, the current state of random disturbance, have a new state S "S" = S+ sign (). delta where given for the step, [-1,1] Random Number