用9*9的矩阵显示字符0~9。 对BP网络进行训练后，可以识别带有一定噪声的字符。...

一个非常酷的机器人的源程序，你可以自己制作你喜欢的机器人并保存起来，很有意思哦(137KB)-A very cool robot of the source, you can own your favorite robot and save up, oh, very interesting (137KB)

遗传算法与工程设计-Genetic Algorithms and Engineering Design

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。

用人工神经网络实现格林码的编码，通过对网络的训练实现，输入一串0/1码得到其格林码-using artificial neural networks Green codes, the network through training, input string of 0/1 yards code to be its Green

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.

SVM-light Version llf_dqy_hhu

一遗传算法的例子源程序-Example of a genetic algorithm source code

这是一个关于目前最前沿课题的神经网络学习模型的程序-xor-This is a topic on the forefront of the current neural network learning procedures for model-xor

JavaGenes is an evolutionary software system written in Java. It implements the genetic algorithm, simulated annealing, stochastic hill climbing and other search techniques.-JavaGenes is an evolutionary software system written in Java. It implements the genetic algorithm, simulated annealing, stochastic hill climbing and other search techniques.

this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) filter to estimate the hidden states of a nonlinear, non-Gaussian state space model.-this demo is to show you how to implement a ge neric SIR (a.k.a. particle, the bootstrap. Monte Carlo) filter to estimate the hidden stat es of a nonlinear. non-Gaussian state space model.