人工智能之八数码难题程序

用java编写的基于小生境的遗传算法，NASG-II，对于用java的朋友来说绝对是个好东西！-Prepared by using java-based niching genetic algorithm, NASG-II, for the friends with java is definitely a good thing!

机器人运动学正解程序,毕业设计可用,希望能有点用场-robical code ，i hope it can be useful for you

这是一个神经网络开发包。目录ann下是专门针对神经网络的代码，外部目录是一些公用的代码，与神经网络无关，但是神经网络的代码用到了它们。 ann目录下有一个目录demo，里面存放了一些示例程序，请参照它们进行编程。 ann/prj/vs7下是编译整个库的Visual Stdudio 2003工程文件-This a neural network development kit. Ann directory under specific neural network code, external directory is some common code, has nothing to do with the neural network, but neural networks use of their code. Ann directory is a directory demo, stored inside a sample program, please refer to their program. Ann/prj/vs7 under compiler for the entire 2003 Visual Stdudio engineering documents

convert a matrix to a libsvm format [class1 char1 char2 ... charN class2 char1 char2 ... charN]

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.

这是一个用MATLAB写的模拟退火算法程序。-This is a written with MATLAB procedure simulated annealing algorithm.

8王后问题的演示程序,算法封装在类GAQueen，演示程序是界面程序-8 queen problem demo program, the algorithm is packaged in a category GAQueen, demo program is the interface procedures

用于m=2 的机器调度问题，可求出最优解与花费的时间-m = 2 for the machine scheduling problems, the optimal solution can be obtained with the time

简单规则演化出来的极似苍蝇的一个人工生命群体floy-simple rules of evolution as same flies an artificial life groups floy

apriori经典算法及一个改进算法的程序,里面有具体的解析与操作-classical apriori algorithm and an improved algorithm for the procedure, there are specific analytical and operational