SVM的一个源程序，功能很强大，实现的结构很巧妙

五子棋是一种受大众广泛喜爱的游戏，这里介绍五子棋程序的数据结构、评分规则、胜负判断方法，重点分析了搜索算法，并在传统的博弈算法在五子棋应用中进行一些改进，从而使剪枝更有效，运算性能更好。改进包括：不使用closed表；改变棋盘搜索顺序；增加记录最大棋盘信息的指针。实验证明，这几点改进对提高效率有很高帮助。

神经网络训练程序，用来进行RBF网络的权值训练，利用训练好的权值可以进行自适应滤波！-neural network training procedures used for RBF network weights training. good use of training weights can be adaptive filtering!

支持向量机完整版（SVM）可以用来进行设别训练-Full version of support vector machine (SVM) can be used to set up other training

粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation).源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary technology (evolutionary computation). Predatory birds originated from the research PSO with similar genetic algorithm is based on iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values. However, there is no genetic algorithm with the cross- (crossover) and the variation (mutation). But particles in the solution space following the optimal particle search. The steps detailed chapter on the future of genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and ot

rhapsody in C++企业解决方案-rhapsody in C++ Enterprise Solutions

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.

关于语音情感识别的一篇论文，里面描述了人工神经网络的方面-Speech Emotion Recognition on a paper, which describes aspects of artificial neural network

这个程序是一个模糊逻辑控制器，用来控制一个简单的水箱模型，比较简单，是我自己设计的，或许能够给大家一些帮助。-This process is a fuzzy logic controller, used to control a simple tank model, relatively simple, is my own design, may be able to give you some help.

我们解决八数码问题,广度优先搜索可能会导致内存不够用,采用启发式搜索,启发函数为f(x)=g(x)+h(x) g(x)为该结点不同于目标结点的个数,h(x)为该结点的深度,选择那f(x)结点最小的那个结点进行扩展, 引入了一个"扩展数组[4]"(因为扩展的结点最多只有4个),该数组保存着某个结点的0点向各个方向的扩展的结点对象,然后对该扩展数组进行分析,利用启发函数在进行递归扩展... -us solve eight digital, BFS may lead to insufficient memory, using heuristic search, heuristic function f (x) = g (x) h (x) g (x) for the target node is different from the number of nodes, h (x) for the nodes of depth, the choice between f (x) nodes that the smallest node expansion. the introduction of an "expanded array [4]" (because the expansion of the nodes at most four), The array maintains a node of 0:00 a.m. to expand in all directions in the target node, and then expanded array analysis, use heuristic function during recursive expansion ...

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