人工神经网络技术在智能分布式检索系统中应用

对支持向量机进行训练的一种改进的遗传算法。-On support vector machine for training an improved genetic algorithm.

松弛算法 批处理裕量松弛算法 样本数据和松弛值自定义-Relaxation Algorithm margin Relaxation Algorithm batch sample data value and relaxation since the definition of

在各种数据源的分析中，收集数据非常重要，本算法提供了一种理论上可以保证性能的聚类算法并提供的相关证明。-Now kneel bowl beat Gou Tai Xu Pleiades cavity中， receive Moreton basin quasi-grind are linked to reset lynx ，算Yang Gou feed leftover braise instance, you can upset Article Sinopodisma殿cavity Abduction Chu Chun Kui Yang算sweet feed cavity gaze intently Shouson殿Longde 。

用隶属函数型神经网与模糊控制融合的解耦程序-Membership functions with neural networks and fuzzy control integration of the decoupling procedure

编写智能电梯仿真系统程序，实现双八层电梯的正常运行-Procedures for the preparation of intelligent elevator simulation system to achieve the normal operation of pairs of eight-story elevator

解非线性规划模型的遗传算法，用c++语言编写，注释完整，结构清晰-Genetic Algorithm for nonlinear programming

聚类CLIQUE算法 的基本思路.zip-clustering algorithm basic ideas. Zip

遗传算法 算法实例MATLAB程序，包括了：选择 变异 交叉 遗传算子-GA

人工神经元的bp算法，可用于函数拟合，时间序列数据的预测，目前应用非常广泛-artificial neurons bp algorithm can be used to function fitting, time series data estimation, is widely used

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