这还是一个蚁群算法实验室,不过内容要更为详细,看得更为清楚,可以用它来理解蚁群的整个觅食过程.-It is also a laboratory ant colony algorithm, but the content should be more detailed, more clearly seen, you can use it to understand the whole feeding process of ant colony.

使用神经网络的K算法来对数据进行分类，有具体的实验要求和图-K using the neural network algorithm to classify the data, there is a specific test requirements and plans

神经网络C程序的第6章-neural network C procedures for the Chapter 6

基本遗传算法的源代码，比较各代种群的进化。-The basic genetic algorithm source code, comparing the generation of species evolution.

混沌识别，混沌特征指数的计算以及混沌预测。-Chaotic identification, chaotic characteristics of index calculation and prediction of chaos.

不确定规划 遗传算法 Goal Programming算法程序- Indefinite plan heredity algorithm Goal Programming algorithm procedure

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

he algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.

遗传算法解决随机期望值模型问题的例题-random genetic algorithms to solve the problem expectations model example

股票交易系统自动根据指标进行相关的交易系统-Automatic stock trading system in accordance with indicators related to the trading system