改程序实现UB算法，对Web日志文件进行分析，产生相似度矩阵

神经网络算法源程序，如ADALINE，提供针对算法的演示源程序-neural network algorithm source, such as ADALINE provide demonstration against the algorithm source code

--- --- --- -人脸检测----------------------Face Detection

蚁群算法：用来进行路径设计、查找、规划等-Ant Colony Algorithm: Path used for design, search, planning, etc.

这是关于人工神经网络的c算法实现，对于算法研究比较有用！-C++ implementation of class network By Luca Cinti and Lorenzo Masetti, based on lightweight neural net library written in C by Peter van Rossum.

基于GA的BP改进算法，用遗传算法对BP 神经网络算法进行改进试用过 里面有数据是可以使用的-GA-based improvement of BP algorithm, genetic algorithm with BP neural network algorithm tried there are data that can be used

基于Hopfield人工神经网路的室内全域路径优化。主要是利用Hopfield求解TSP的方法。用于课程设计。-based on artificial neural network Hopfield indoor entire domain path optimization. Hopfield is mainly used for TSP method. For course design.

该算法经运行，无任何问题，可用于解决遗传算法求解车辆路线问题-The algorithm by running without any problems, can be used for genetic algorithm to solve Vehicle Routing Problem

利用逻辑编程语言prolog的空间关系组合推理程序。利用的理论是约束处理规则，和空间关系表示 -use logic programming language prolog combination of the spatial relationships reasoning process. The theory is the use of binding rules, and spatial relations

Code for Truth Maintenance System in Artificial Intelligence.-Code for Truth Maintenance System in Artificial Intelligence.

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