这是神经网络和遗传算法想结合的c++程序，希望对需要的朋友 有所帮助。...

人工智能是现在科学发展的热门，该程序通过人工神经网络的原理实现图像的分类功能-The scientific development of artificial intelligence is now the most popular, the program adopted the principle of artificial neural network classification of image features

介绍了在LabView环境下的神经网络算法-Introduced in the LabView environment, the neural network algorithm

关于鱼群算法的一个程序，希望对学习智能算法的朋友有所帮助。-Fish-swarm algorithm on a procedure, and they hope to learn from intelligent algorithm friend help.

由于K－均值聚类算法局部最优的特点，而模拟退火算法理论上具有全局最优的特点。因此，用模拟退火算法对聚类进行了改进。20组聚类仿真表明，平均每次对K结果值改进8次左右，效果显著。下一步工作：实际上在高温区随机生成邻域是个组合爆炸问题（见本人上载软件‘k－均值聚类算法’所述），高温跳出局部解的概率几乎为0，因此正考虑采用凸包约束进行模拟聚类，相关工作正在进行。很快将奉献给各位朋友。-as K-means clustering algorithm for optimal local characteristics, and simulated annealing algorithm theory with the characteristics of the global optimum. Thus, simulated annealing algorithm for clustering improvements. Cluster Group of 20 simulations show that the average value of K results improved about eight times, the results are obvious. The next step : In fact, in high temperature generated random neighborhood is a combination of explosives (see my software on the "k-means clustering algorithm" mentioned above), high-temperature solution of partial out almost zero probability, it is considering the use of convex hull bound for simulation cluster, the work under way . Soon dedication to the ladies.

pre-fixSpan算法，该算法是C++语言实现的，主要用模板实现prefixspan的投影数据库架构及模式生长功能

小波神经网络，两者相互结合，程序简洁易懂！-Wavelet neural network, the two interact and procedures easier to understand!

用于求解TSP的蚁群算法，C 语言 已经运行过-Basic Ant Colony Algorithm for TSP

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

蚂蚁算法的VC代码源，模拟蚂蚁觅食的行走途径，解决最优路径问题。-Ant Algorithm VC source code to simulate the foraging ants to walk way to solve the optimal routing problem.

一个VC编写的神经网络算法程序，对学智能算法的朋友很有用。-a VC prepared by the neural network algorithm procedures, intelligent algorithm friends useful.