用BP网络实现对图像的边缘进行提取，本程序为演示程序，可以看到BP在应用中的效果...

这是一个二值hopfield神经网络源程序，有一个实例，训练数据保存在h7x8n4.trn,输出数据保存在ARCHIVE.LST中。-This is a value hopfield two neural network source, an example of training data stored in h7x8n4.trn, output data stored in ARCHIVE.LST China.

多目标进化算法源代码-more evolutionary algorithm source code

改进遗传算法程序-improved genetic algorithm program

一个神经网络小脑CMACmatlab算法例子- A nerve network cerebellum CMACmatlab algorithm example

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

粒子群寻优算法源程序，采用VC+=编写， 比较好用。-Particle

用遗传算法实现任务分配优化的源程序。-genetic algorithm optimization task allocation of the source.

maltab 的一个遗传算法的例子,比较全,有教你怎么初始化初始种群,设定参数,还有demo提供学习-A genetic algorithm using maltab gentitc toolbox ,abundant in content.Whats s more, you are teached how to initialize the initial population, set parameters. It also provide learning demos.

用BP神经网络逼近函数Z=SIN(X*Y),采用C++编程.-Using BP neural network to approach the function Z = SIN (X* Y), using C++ programming.

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