自已用C++写的手势辨识,可分出四个不同的手势。

主要实现了烧结矿碱度的神经网络预测，训练精度高-The main achievement of the sinter basicity of the neural network prediction, training and high precision

ClustanGraphics聚类分析工具。提供了11种聚类算法。 Single Linkage (or Minimum Method, Nearest Neighbor) Complete Linkage (or Maximum Method, Furthest Neighbor) Average Linkage (UPGMA) Weighted Average Linkage (WPGMA) Mean Proximity Centroid (UPGMC) Median (WPGMC) Increase in Sum of Squares (Ward s Method) Sum of Squares Flexible (ß space distortion parameter) Density (or k-linkage, density-seeking mode analysis) -ClustanGraphics clustering analysis tools. Provides 11 kinds of clustering algorithms. Single Linkage (or Minimum Method, Nearest Neighbor) Complete Linkage (or Maximum Method, Furthest Neighbor) Average Linkage (UPGMA) Weighted Average Linkage (WPGMA) Mean ProximityCentroid (UPGMC) Median (WPGMC) Increase in Sum of Squares (Ward s Method) Sum of SquaresFlexible (? space distortion parameter) Density (or k-linkage, density-seeking mode analysis)

用遗传算法进行排序-genetic sequencing algorithms

基于VC++的遗传算法源码（相当经典），非常可观-Based on VC++ Genetic algorithm source code (very classic), very impressive

Fisher线性判别分类器应用于IRIS数据集的例子-An example of Fisher linear discriminant Classifier applied on IRIS Data Set

模式识别与人工智能中经典算法younger算法的实现及应用-Pattern Recognition and Artificial Intelligence in the classical algorithm younger Algorithm and Application

使用模拟退火思想解决ISP（独立集）问题，使用先看说明-Thinking of using the simulated annealing solution to ISP (independent set), the use of look at the description

人工智能神经网络算法的实现。注意可能由于实现方式不同而导致结果有点不一样，这是允许的。-Artificial neural network algorithm.

K-均值聚类算法的编程实现。包括逐点聚类和批处理聚类。K－均值聚类的的时间复杂度是n*k*m，其中n为样本数，k为类别数，m为样本维数。这个时间复杂度是相当客观的。因为如果用每秒10亿次的计算机对50个样本采用穷举法分两类，寻找最优，列举一遍约66.7天，分成3类，则要约3500万年。针对算法局部最优的缺点，本人正在编制模拟退火程序进行改进。希望及早奉给大家，倾听高手教诲。-K-means clustering algorithm programming. Point by point, including clustering and clustering batch. K-means clustering of the time complexity of n* k* m, n samples, several types of k, m sample dimension. The time complexity is a very objective. Because if we use one billion times per second the computer using 50 samples of two exhaustive method to find the optimal set out again about 66.7 days, divided into three categories, offering 3,500 years. Local optimal algorithm against the shortcomings, I was prepared simulated annealing process improvements. Early Feng hope for everyone, listen to the master teachings.

用遗传算法求解背包问题是南京航空航天大学信息与计算科学专业编写的.本程序利用遗传算法来求解背包问题.采用二进制字符串编码,1表示选择物体,0则不选择. 背包问题描述:在M件物品取出若干件放在空间为W的背包里，每件物品的重量为W1，W・2……Wn，与之相对应的价值为P1,P2……Pn。求出获得最大价值的方案。注意：在本题中，所有的重量值均为整数。-genetic algorithm knapsack problem is the Nanjing University of Aeronautics and Astronautics, Information and Computing Science prepared. The procedure the use of genetic algorithms to solve knapsack problem. binary string encoding, an option objects, 0 no choice. Knapsack Problem Description : M items removed several pieces on the space-W backpack, Each of the weight W1, W 2 ... Wn, the corresponding value of P1, P2 ... Pn. Sought to gain maximum value of the program. NOTE : In this issue, all the weight values are integers.