基于基本遗传算法的函数最优化，C++源代码

face recognition test source code

粒子群算法，希望对大家有用，粒子群算法粒子群算法-PSO, a member of the useful, PSO PSO

对于学习混沌理论的人很有用的，这也是搜集到的-Chaos Theory for the study were very useful, which is collected

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

K-均值聚类算法的编程实现。包括逐点聚类和批处理聚类。K－均值聚类的的时间复杂度是n*k*m，其中n为样本数，k为类别数，m为样本维数。这个时间复杂度是相当客观的。因为如果用每秒10亿次的计算机对50个样本采用穷举法分两类，寻找最优，列举一遍约66.7天，分成3类，则要约3500万年。针对算法局部最优的缺点，本人正在编制模拟退火程序进行改进。希望及早奉给大家，倾听高手教诲。-K-means clustering algorithm programming. Point by point, including clustering and clustering batch. K-means clustering of the time complexity of n* k* m, n samples, several types of k, m sample dimension. The time complexity is a very objective. Because if we use one billion times per second the computer using 50 samples of two exhaustive method to find the optimal set out again about 66.7 days, divided into three categories, offering 3,500 years. Local optimal algorithm against the shortcomings, I was prepared simulated annealing process improvements. Early Feng hope for everyone, listen to the master teachings.

模式识别中isodata的 vc++实现-pattern recognition isodata achieve the vc

生产线上的上车数量注册软件的部分源代码，用于注册杭车数量，以便进行自动控制-The production line picking up the number of registered software, part of the source code used to register Hang cars for automatic control

神经网络模式识别及其实现，第八章。 内含：KMEANS 、KOHONEN 、LVQ 、SOFM 算法。-pattern recognition and neural network to achieve, Chapter VIII. Intron : KMEANS, KOHONEN, LVQ, SOFM algorithm.

这是一个聚类代码，里面有分类数据，有MAKEFILE，可以实现模式的分类中-This is a clustering source code which contains classfication data and MAKEFILE.It can be used in classifying pattens.

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